Methods for providing monitoring data to detect movable objects, methods for detecting movable objects, methods and apparatus for creating at least one predefined point-symmetric region.

Abstract

The present invention relates to a method for providing surveillance data (135) to detect a movable object (100). The method includes the step of reading image data (105) provided by means of a camera (102). The image data (105) represents a camera image of the environment of the camera (102), wherein at least one predefined even- and / or odd-point symmetric region (110) is arranged in the field of view of the camera (102), wherein, from the perspective of the camera (102), the at least one predefined even- and / or odd-point symmetric region (110) can be at least partially occluded by the movable object (100). The method further includes the step of using the image data (105) and a determination rule (128) to determine the presence of at least one center of symmetry (112) of the at least one even- and / or odd-point symmetric region (110) to determine the occlusion state of the at least one predefined even- and / or odd-point symmetric region (110) by the movable object (100). The monitoring data (135) is provided based on the occlusion status.

Description

Technical Field

[0001] This invention is based on the apparatus or method of the type claimed in the independent claims. Computer programs are also the subject of this invention. Background Technology

[0002] Traditional gratings can use narrow beams of light, and the interruption of this beam by an object entering it can be detected by a sensor. The light source and sensor can be arranged on opposite sides of the area to be monitored. Another traditional design is the reflective grating. Here, the light source and sensor are arranged on the same side, for example, within a common housing. Back reflectors can be arranged on opposite sides, reflecting the light back in the direction it was emitted. Both of these classic forms require their own light source, and therefore are active systems in this sense. The beam used can be visible or can be made visible, for example, by means of fog and infrared cameras, if it is an infrared grating.

[0003] The later-published DE 102020202160A1 discloses a method for determining symmetry properties in image data and a method for controlling functions. Summary of the Invention

[0004] Against this backdrop, the proposed solution here provides a method according to the main claim, an apparatus for using the method, and a corresponding computer program. Advantageous extensions and improvements can be made to the apparatus described in the independent claim through the measures listed in the dependent claims.

[0005] According to the implementation method, in particular, the fact that points or objects in the world are marked or will be marked by means of point-symmetric regions can be utilized, enabling systems with imaging sensors and suitable methods proposed herein to detect and locate these point-symmetric regions with high precision in order to robustly and locally perform specific technical functions, optionally without being perceived as interference by humans or organisms.

[0006] For example, a symmetrical region might not be fully imaged into the camera image, for instance, because it might be partially occluded by an object, partially protrude from the image, or be cropped. Advantageously, the accuracy of the point's center of symmetry can still be maintained because partial occlusion does not distort its position: the remaining point symmetry pairs can still vote for the correct center of symmetry. Partial occlusion only reduces the strength of clustered points in the voting matrix, but the position of the center of symmetry can be preserved and still determined accurately and easily. This is a special advantage of utilizing point symmetry.

[0007] Further advantages in finding regions or patterns based on point symmetry can stem particularly from the fact that point symmetry is invariant with respect to rotation between the point-symmetric region and the camera or image recording, and is largely invariant with respect to the viewing angle. For example, the point-symmetric plane can be invariant with respect to affine imaging. The imaging of an arbitrarily oriented plane by a real camera can always be approximated well, at least locally, by affine imaging. For example, if a circular point-symmetric region is viewed from an oblique angle, the circle becomes an ellipse, in which the point symmetry characteristics and the center of point symmetry are preserved. Therefore, at least one point-symmetric region does not necessarily have to be viewed from a frontal view—even a very oblique viewpoint will not pose a difficulty, and achievable accuracy can be maintained. This invariance, especially with respect to rotation and with respect to the viewing angle, eliminates the need for precautions such as properly aligning the camera with the symmetric region or vice versa. Rather, it may be sufficient that the corresponding point-symmetric region is at least partially captured in the camera image, making it detectable. The relative positional relationship or arrangement between the point-symmetric region and the camera can be insignificant or almost insignificant in this case.

[0008] This invention proposes a method for providing surveillance data to detect movable objects, wherein the method comprises the following steps:

[0009] Image data provided by the camera is read from an interface to the camera, wherein the image data represents a camera image of the environment of the camera, wherein at least one predefined even- and / or odd-numbered point-symmetric region in the environment is arranged in the field of view of the camera, wherein, from the perspective of the camera, the at least one predefined point-symmetric region can be at least partially occluded by the movable object; and

[0010] The presence of at least one center of symmetry of the at least one even- and / or odd-numbered point symmetric region in the camera image is determined using the image data and determination rules to determine the occlusion state of the movable object on the at least one predefined even- and / or odd-numbered point symmetric region, wherein the monitoring data is provided based on the occlusion state.

[0011] This method can be implemented, for example, in software or hardware, or a hybrid of software and hardware, such as in a control device or apparatus. At least one predefined point-symmetric region can be manufactured by performing a variation of the method described below for manufacturing. In the read-in step, image data can also be read from multiple cameras, wherein these image data can represent multiple camera images of at least one predefined even- and / or odd-point-symmetric region. The determination rules can be similar to or correspond to the process disclosed in DE 102020202160, which was later disclosed by the applicant.

[0012] According to one embodiment, the determination rule used in the determination step can be configured such that signatures are generated for multiple pixels of at least one segment of the camera image to obtain multiple signatures. In this case, each signature can be generated using a descriptor having multiple different filters. Each filter can have at least one symmetry type. Each signature can have a symbol for each filter of the descriptor. The determination rule can also be configured such that at least one mirror signature for at least one symmetry type used for the filter is determined for the signature. The determination rule can also be configured such that it is checked whether at least one additional pixel with a signature is present in a search area in the environment surrounding the pixel, to determine the pixel coordinates of at least one symmetry signature pair from the pixel and the additional pixel when the at least one additional pixel is present. In addition, the determination rule can be configured such that the pixel coordinates of the at least one symmetry signature pair are evaluated to identify the at least one symmetry center. The descriptor can describe the image content in the local environment surrounding the pixel or reference pixel in a compact form. The signature can, for example, represent the value of the descriptor describing the pixel in binary. Therefore, multiple calculated signature images can be used to determine the at least one mirrored signature; for example, one signature image with a normal filter, one signature image with an even-numbered point mirror filter, and one signature image with an odd-numbered point mirror filter. Additionally or alternatively, at least one reflector can be applied to the symbols of one of the signatures to determine at least one mirrored signature. In this case, each reflector can have rules for modifying the symbols, specific to the symmetry type and dependent on the descriptor. Here, the search area can depend on at least one of the applied reflectors. Such an implementation provides the advantage of enabling efficient and accurate detection of symmetry features in image data. In this case, symmetry detection in an image can be achieved with minimal effort.

[0013] Here, in the determination step, for each determined center of symmetry, using the pixel coordinates of each symmetry signature pair that helps to correctly identify the center of symmetry, a transformation rule is determined for transforming the pixel coordinates of the center of symmetry and / or at least one predefined even- and / or odd-numbered point symmetry region. This transformation rule can be applied to the pixel coordinates of the center of symmetry and / or at least one predefined even- and / or odd-numbered point symmetry region to correct the distorted viewpoint of the camera image. The advantage of this implementation is that it allows for reliable and accurate reconstruction of the correct mesh or correct topology for multiple point symmetry regions.

[0014] Furthermore, the method may include the following steps: comparing at least one center of symmetry from the camera image with at least one reference center of symmetry from reference data in terms of intensity, intensity variation over time, and / or local intensity variation to determine an intensity-related deviation between the center of symmetry and the reference center of symmetry. In this case, the monitoring data is provided based on the deviation. The reference data may represent information about the reference center of symmetry or a reference image. The reference data or the reference image may be selected from a plurality of stored reference data or reference images, or generated using stored generation rules. The deviation may be determined with respect to the intensity or response of symmetry detection for the corresponding center of symmetry, which may be measured as weight or height, or height after convergence smoothing. In particular, the deviation may be determined based on the change of one or more responses over time.

[0015] The symmetry type of the at least one symmetry center can also be determined in the determination step. The symmetry type can represent even-numbered point symmetry and additionally or alternatively, odd-numbered point symmetry. Additionally or alternatively, in this case, in the comparison step, the symmetry type of the at least one symmetry center in the camera image can be compared with a predefined symmetry type of at least one reference symmetry center from reference data to check the consistency between the at least one symmetry center and the at least one reference symmetry center. Odd-numbered point symmetry can be generated by mirroring points with inverted grayscale or color values. By using and identifying two different point symmetries, the information content of the point symmetry region and pattern can be increased.

[0016] In this case, the image data read in the read-in step can represent a camera image of at least one pattern consisting of multiple predefined even- and / or odd-numbered symmetrical regions. Here, in the determination step, the geometric arrangement of the symmetry centers of the at least one pattern can be determined, a geometric sequence of the symmetry types of the symmetry centers can be determined, and additionally or alternatively, the pattern can be determined from multiple predefined patterns using the sequence. The arrangement and / or the sequence can represent an identification code for the pattern. This implementation offers the advantage of increased reliability in identifying symmetry centers and the ability to obtain further information by recognizing specific patterns. Reliable identification of symmetry centers can also be achieved for different distances between the camera and the pattern.

[0017] In this scenario, during the determination step, the arrangement of the symmetry centers of the at least one pattern, along with, additionally or alternatively, a sequence of symmetry types of the symmetry centers, is used to determine implicit additional information about the at least one pattern, or readout rules for reading explicit additional information from the camera image. The arrangement and, additionally or alternatively, the sequence can represent the additional information in an coded form. The additional information can be related to the detection of a moving object. This implementation provides the advantage of conveying additional information through the topology of at least one pattern.

[0018] Furthermore, the determination steps and additional or alternative comparison steps can be performed jointly for all centers of symmetry, independent of their symmetry type, or the determination steps and additional or alternative comparison steps can be performed individually for centers of the same symmetry type, depending on their symmetry type. Therefore, joint execution allows for accurate and reliable identification of centers of symmetry with low memory and time requirements. Optionally, and particularly in particular, individual execution can minimize confusion with randomly occurring patterns in the image.

[0019] A method for detecting movable objects is also proposed, which includes the following steps:

[0020] Evaluate the monitoring data provided according to the implementation of the above method to generate a detection signal dependent on the monitoring data; and

[0021] The detection signal is output to the interface of the processing unit used to perform the grating function in order to perform the detection of the movable object.

[0022] This method can be implemented, for example, in software or hardware, or a hybrid of software and hardware, such as in a control device or apparatus. Here, the implementation methods described above for providing the method can be advantageously combined to perform the detection method.

[0023] Furthermore, a method is proposed for manufacturing at least one predefined even- and / or odd-point symmetric region for use in embodiments of the above method, wherein the method comprises the following steps:

[0024] Generate design data, which represents a graphical representation of the at least one predefined symmetrical region of even and / or odd points; and

[0025] The design data is used to generate the at least one predefined even and / or odd point symmetrical region on, at, or within the display medium to create the at least one predefined even and / or odd point symmetrical region.

[0026] This method can be implemented, for example, in software or hardware, or a hybrid of software and hardware, such as in a control device or apparatus. By performing this manufacturing method, at least one predefined even- and / or odd-numbered point symmetrical region can be manufactured, which can be used within the scope of the embodiments of the above-described method.

[0027] According to one embodiment, design data can be generated in the generation step, said design data being a graphical representation of at least one predefined even- and / or odd-numbered point symmetrical region represented by a circle, ellipse, square, rectangle, pentagon, hexagon, polygon, or annulus. In this case, the at least one predefined even- and / or odd-numbered point symmetrical region can have a regular or quasi-random content pattern. Additionally or alternatively, a first half of the at least one predefined even- and / or odd-numbered point symmetrical region can be arbitrarily predefined, and a second half can be constructed by dot mirroring and optionally additionally inverting grayscale values ​​and additionally or alternatively inverting color values. Additionally or alternatively, in the generation step, the at least one predefined even- and / or odd-numbered point symmetrical region can be generated by additive manufacturing processes, separation, coating, forming, initial forming, or optical display. Additionally or alternatively, the display medium can be glass, stone, ceramic, plastic, rubber, metal, concrete, plaster, paper, cardboard, food, or an optical display device. Therefore, at least one predefined even and / or odd point symmetric region can be manufactured in a suitable manner, depending on the specific purpose or application and the general boundary conditions therein.

[0028] Design data representing a graphical representation of at least one pattern composed of multiple predefined even- and / or odd-point symmetrical regions can also be generated in the generation step. In this case, at least a subset of the even- and / or odd-point symmetrical regions may be aligned on a regular or irregular grid, directly adjacent to each other, and additionally or alternatively separated from at least one adjacent even- and / or odd-point symmetrical region by gaps. They may be identical or different from each other in terms of their size and / or their content patterns, and additionally or alternatively arranged in a common plane or different planes. Additionally or alternatively, in the generation step, design data representing a graphical representation of at least one pattern with layered symmetry can be generated. In this way, different patterns with specific information content and additionally or alternatively patterns with layered symmetry can be generated for different distances from the pattern.

[0029] Even when corresponding markings are known to exist, it is particularly difficult for humans to perceive the symmetry hidden within a pattern. This, for example, makes it possible to conceal such markings. This may be meaningful or desirable for various reasons, such as aesthetic reasons, because technical markings should not or do not wish to be seen, for example, because attention should not be diminished by markings that are unimportant to humans, or because the markings should be kept confidential. Aesthetic reasons play an important role, especially in the field of design. For example, in the interior space of a vehicle, on the exterior of a vehicle, on an aesthetically pleasing object, or in the field of internal or architectural architecture, conspicuous technical markings are not or are difficult to accept. However, if technical markings are to be concealed, for example, in fabric patterns, or in plastic or ceramic reliefs, or in holograms, or on printed surfaces, as may be possible according to the implementation, the technical markings can be both aesthetically pleasing and useful, for example, providing one or more reference points for a camera, so as to determine, for example, the relative camera pose. Depending on the application, the concealed aspects may also be irrelevant or have little or no relevance. Thus, the robustness of the technology still applies to the use of such designed patterns. In particular, patterns with random or pseudo-random characters can provide a variety of possibilities for finding as clearly defined pairs of symmetrical points as possible. According to the implementation, this can be utilized, for example, particularly to improve the signal-to-noise ratio of the response measured at the center of symmetry, and thus to improve robustness in the sense of error-free detection and precise localization of the center of symmetry. The pattern may, in particular, comprise one or more point-symmetric regions having odd or even point symmetry. These regions may be designed, for example, as circles, hexagons, squares, ellipses, polygons, or other shapes. The point-symmetric regions may be of the same type or of different shapes and sizes. The point-symmetric regions may be connected to each other without gaps or spaced apart.

[0030] The proposed solution also creates a device configured to perform, manipulate, or implement variations of the methods presented herein within a corresponding apparatus. The task on which this invention is based can also be solved quickly and efficiently through this embodiment of the invention in the form of a device.

[0031] To this end, the device may have at least one computing unit for processing signals or data, at least one storage unit for storing signals or data, at least one interface to a sensor or actuator, at least one communication interface for reading sensor signals from the sensor or for outputting data or control signals to the actuator, and / or for reading or outputting data embedded in a communication protocol. The computing unit may be, for example, a signal processor, a microcontroller, etc., and the storage unit may be flash memory, EEPROM, or magnetic storage. The communication interface may be configured to wirelessly and / or wiredly read or output data, wherein a communication interface capable of reading or outputting wired data may, for example, electrically or optically read the data from a corresponding data transmission line or electrically or optically output the data to a corresponding data transmission line.

[0032] In the current context, a device can be understood as an electrical apparatus that processes sensor signals and outputs control signals and / or data signals based on those signals. The device may have an interface that can be configured as hardware and / or software. When configured as hardware, the interface may, for example, be part of a so-called system ASIC that contains various functions of the device. However, the interface may also be a separate integrated circuit or at least partially composed of discrete components. When configured as software, the interface may be a software module that exists, for example, on a microcontroller along with other software modules.

[0033] A system for detecting movable objects is also proposed, wherein the system has the following characteristics:

[0034] One embodiment of the above-mentioned equipment;

[0035] At least one camera, wherein the camera and the device are or have been connected to each other in a manner capable of transmitting data; and

[0036] At least one predefined even- and / or odd-numbered point symmetrical region is manufactured according to an embodiment of the aforementioned manufacturing method, wherein the region can or has been arranged in the field of view of the camera.

[0037] In this case, the system can provide the function of a grating.

[0038] A computer program product or computer program having program code is also advantageous. This program code can be stored on a machine-readable carrier or storage medium (such as semiconductor memory, hard disk storage, or optical memory) and is used to execute, implement, and / or manipulate the steps of the method according to one of the above embodiments, particularly when the program product or program is running on a computer or device. Here, the method can be implemented as a hardware accelerator on a SoC or ASIC. Attached Figure Description

[0039] Embodiments of the proposed scheme are shown in the accompanying drawings and explained in more detail in the following description.

[0040] Figure 1 An embodiment of the device for provision, an embodiment of the device for detection, and a schematic diagram of a camera are shown;

[0041] Figure 2 A schematic diagram of an embodiment of the equipment used for manufacturing is shown;

[0042] Figure 3 A flowchart illustrating an embodiment of the provided method is shown;

[0043] Figure 4 A flowchart illustrating an embodiment of the method for detection is shown.

[0044] Figure 5 A flowchart illustrating an embodiment of the method for manufacturing is shown;

[0045] Figure 6 A schematic diagram of a display medium having a pattern composed of predefined point symmetrical regions is shown according to an embodiment;

[0046] Figure 7 A schematic diagram of a display medium having a pattern composed of predefined point symmetrical regions is shown according to an embodiment;

[0047] Figure 8 It shows that it has a source Figure 7 A schematic diagram of a display medium for a pattern, highlighting a pattern or a predefined point symmetrical area;

[0048] Figure 9 A schematic diagram of a predefined point-symmetric region according to an embodiment is shown;

[0049] Figure 10 A schematic diagram of a pattern composed of predefined point-symmetric regions is shown according to an embodiment;

[0050] Figure 11 A schematic diagram illustrating the use of a lookup table according to an embodiment is shown;

[0051] Figure 12 A schematic diagram of a voting matrix according to an embodiment is shown;

[0052] Figure 13 A schematic diagram illustrating an exemplary pattern arranged in a cube-like form according to an embodiment, showing the correct identification of the grid;

[0053] Figure 14 Shown from an oblique perspective Figure 6The first part of the illustration is a schematic diagram of the pattern shown.

[0054] Figure 15 Showing from Figure 14 The first part of the illustration shows a pattern in which a predefined point-symmetric region is highlighted;

[0055] Figure 16 An example is shown. Figure 15 A schematic diagram of the pattern after viewpoint correction;

[0056] Figure 17 A schematic diagram of an embodiment with a layered symmetrical pattern is shown;

[0057] Figure 18 A schematic diagram of an embodiment with a layered symmetrical pattern is shown;

[0058] Figure 19 A schematic diagram of an embodiment with a layered symmetrical pattern is shown;

[0059] Figure 20 A schematic diagram of a pattern according to an embodiment is shown;

[0060] Figure 21 A schematic diagram illustrating the detection status using a predefined point-symmetric region according to an embodiment is shown;

[0061] Figure 22 A schematic diagram illustrating the detection status using a pattern composed of predefined point symmetrical regions according to an embodiment is shown.

[0062] Figure 23 A schematic diagram illustrating the detection status using a pattern composed of predefined point symmetrical regions according to an embodiment is shown.

[0063] Figure 24 A schematic diagram illustrating the detection status using a pattern composed of predefined point-symmetric regions according to an embodiment is shown; and

[0064] Figure 25 A schematic diagram illustrating the detection status using a pattern composed of predefined point symmetrical regions according to an embodiment is shown. Detailed Implementation

[0065] In the following description of advantageous embodiments of the invention, the same or similar reference numerals are used for elements shown in different figures and having similar effects, wherein repeated descriptions of these elements are omitted.

[0066] Figure 1 Embodiments of the device 120 for provision, embodiments of the device 140 for detection, and schematic diagrams of the camera 102 (exemplary only) are shown. Figure 1In the illustrations, the providing device 120 or the providing device 120 and the detection device 140 or the detection device 140 are shown separately or arranged externally to the camera 102. The providing device 120 and the detection device 140 are connected to the camera 102 in a manner capable of data transmission. According to another embodiment, the providing device 120 and / or the detection device 140 may also be part of the camera 102 and / or may be combined with each other.

[0067] Camera 102 is configured to record camera images of its environment. Within the environment of camera 102, exemplarily only predefined even- and / or odd-numbered point symmetrical regions 110 with a center of symmetry 112 are arranged within the field of view of camera 102. From the camera's perspective, at least one predefined even- and / or odd-numbered point symmetrical region 110 may be at least partially occluded by a movable object 100. Camera 102 is also configured to provide or generate image data 105 representing a camera image, wherein the camera image also shows the predefined even- and / or odd-numbered point symmetrical regions 110 and / or the movable object 100.

[0068] The providing device 120 is configured to provide monitoring data 135 for detecting moving objects. For this purpose, the providing device 120 includes a reading device 124, a determining device 126, and optionally an execution device 130. The reading device 124 is configured to read image data 105 from the providing device 120 through an input interface 122 to the camera 102. Furthermore, the reading device 124 is also configured to forward the image data 105 representing a camera image to the determining device 126.

[0069] The determining device 126 of the providing device 120 is configured to use image data 105 and determining rule 128 to determine the presence of the center of symmetry 112 of at least one point symmetric region 110 in the camera image, in order to determine the occlusion state of the movable object 100 on at least one predefined even and / or odd point symmetric region 110. Determining rule 128 will be discussed in more detail below. It should be noted that determining rule 128 is similar to or corresponds to the process disclosed in DE 102020202160, which was later disclosed by the applicant. The providing device 120 is configured to provide monitoring data 135 based on the occlusion state. More precisely, the providing device 120 is configured to provide monitoring data 135 to the detection device 140 via the output interface 138 of the providing device 120.

[0070] According to one embodiment, the determining device 126 is configured to forward at least one determined center of symmetry 112 and / or occlusion state to the execution device 130. The execution device 130 is configured to compare the position of at least one center of symmetry 112 in a camera image with at least one reference center of symmetry from reference data 115 in terms of intensity, intensity variation over time, and / or local intensity variation, to determine an intensity-related deviation 131 between the center of symmetry 112 and the reference center of symmetry. The execution device 130 is also configured to read in or receive reference data 115 from a storage device 150. The storage device 150 may be implemented as part of or separate from the providing device 120. In this case, the providing device 120 is configured to use the deviation 131 to provide monitoring data 135.

[0071] The detection device 140 is configured to detect a movable object 100. For this purpose, the detection device 140 includes an evaluation device 144 and an output device 146. The detection device 140 is configured to receive or read monitoring data 135 from the providing device 120 via an input interface 142. The evaluation device 144 is configured to evaluate the monitoring data 135 provided by the providing device 120 to generate a detection signal 145 dependent on the monitoring data 135. The evaluation device 144 is also configured to forward the detection signal 145 to the output device 146. The output device 146 is configured to output the detection signal 145 to an output interface 148 of a processing unit that performs a grating function to perform the detection of the movable object 100.

[0072] Specifically, determination rule 128 is configured such that signatures are generated for multiple pixels of at least one segment of the camera image to obtain multiple signatures. In this case, each signature is generated using a descriptor with multiple different filters. Each filter has at least one symmetry type. Each signature has a symbol for each filter of the descriptor. Determination rule 128 can also be configured such that at least one reflector is applied to the symbol of one of the signatures to determine at least one mirror signature for at least one symmetry type of the filter for that signature. In this case, each reflector includes a symmetry type-specific and descriptor-dependent filter rule for modifying the symbol. Determination rule is also configured such that it is checked whether a pixel with a signature exists in a search area in the environment surrounding that pixel, depending on the applied at least one reflector, and that at least one additional pixel has a signature corresponding to at least one mirror signature, to determine the pixel coordinates of at least one symmetry signature pair from that pixel and the additional pixel when the at least one additional pixel exists. Additionally, determination rule is configured such that the pixel coordinates of the at least one symmetry signature pair are evaluated to identify the at least one symmetry center.

[0073] According to one embodiment, the determining device 126 is configured to generate, for each determined center of symmetry 112, a transformation rule for transforming the pixel coordinates of the center of symmetry 112 and / or the point symmetry region 110 using pixel coordinates that help correctly identify the center of symmetry 112. The transformation rule is applied to the pixel coordinates of the center of symmetry 112 and / or the point symmetry region 110 to correct for distorted viewpoints in the camera image. Furthermore, it is advantageous to determine the transformation rule based on multiple, particularly adjacent, point symmetry regions 110, as this is more robust, more accurate, and less affected by noise, especially if these point symmetry regions lie in a common plane. The application of the transformation is particularly advantageous when considering the arrangement of multiple centers of symmetry 112.

[0074] According to one embodiment, the determining device 126 is further configured to determine the symmetry type of at least one symmetry center 112. This symmetry type represents even-numbered point symmetry and additionally or alternatively represents odd-numbered point symmetry. Additionally or alternatively, in this case, the executing device 130 is configured to compare the symmetry type of at least one symmetry center 112 in the camera image with a predefined symmetry type of at least one reference symmetry center from reference data 115 to check for consistency between at least one symmetry center 112 and at least one reference symmetry center.

[0075] Specifically, image data 105 in this case represents a camera image of at least one pattern composed of multiple predefined point symmetry regions 110. Here, determining device 126 is configured to determine the geometric arrangement of the symmetry centers 112 of at least one pattern, determine the geometric sequence of the symmetry types of the symmetry centers 112, and / or use said sequence to determine the correct pattern represented by image data 105 from multiple predefined patterns. This arrangement and / or the sequence may represent an identification code of the pattern. According to one embodiment, determining device 126 in this case is configured to use the arrangement of the symmetry centers 112 of at least one pattern and / or the sequence of the symmetry types of the symmetry centers 112 to determine implicit additional information of the at least one pattern or readout rules for reading explicit additional information in the camera image. This arrangement and / or the sequence represents the additional information in coded form. The additional information relates to the detection of a movable object.

[0076] Figure 2 A schematic diagram of an embodiment of a manufacturing apparatus 200 is shown. The manufacturing apparatus 200 is configured to manufacture at least one predefined even- and / or odd-numbered point symmetric region 110 for use in manufacturing processes. Figure 1 The provision of equipment or similar equipment and / or Figure 1The apparatus 200 for manufacturing includes a generating device 202 and a producing device 206. The generating device 202 is configured to generate design data 204. The design data 204 represents a graphical representation of at least one predefined even- and / or odd-numbered point symmetric region 110. The producing device 206 is configured to use the design data 204 to produce at least one predefined even- and / or odd-numbered point symmetric region 110 on, at, or within a display medium, thereby manufacturing at least one predefined even- and / or odd-numbered point symmetric region 110.

[0077] According to one embodiment, the generating device 202 is configured to generate design data 204, which is a graphical representation of at least one predefined even- and / or odd-numbered point symmetric region 110 represented by a circle, ellipse, square, rectangle, pentagon, hexagon, polygon, or annulus. The at least one predefined even- and / or odd-numbered point symmetric region 110 has a regular or quasi-random content pattern, and / or a first half-face of any predefined even- and / or odd-numbered point symmetric region 110 is pre-given, and a second half-face is constructed by dot mirroring and / or inversion of grayscale and / or color values. Additionally or alternatively, the generating device 206 is configured to generate at least one predefined even- and / or odd-numbered point symmetric region 110 by additive manufacturing processes, separation, coating, molding, initial forming, or optical display. Additionally or alternatively, the display medium in this case is glass, stone, ceramic, plastic, rubber, metal, concrete, plaster, paper, cardboard, food, or an optical display device.

[0078] According to one embodiment, the generating device 202 is configured to generate design data 204 representing a graphical representation of at least one pattern composed of a plurality of predefined even- and / or odd-numbered point-symmetric regions 110, wherein at least one subset of the point-symmetric regions 110 are aligned on a regular or irregular grid, directly adjacent to each other and / or separated from at least one adjacent point-symmetric region 110 by gaps, are the same as or different from each other in terms of their size and / or their content patterns, and / or are arranged in a common plane or in different planes. Additionally or alternatively, the generating device 202 is configured to generate design data 204 representing a graphical representation of at least one pattern having layered symmetry.

[0079] Figure 3 A flowchart illustrating an embodiment of a method 300 for providing monitoring data to detect movable objects is shown. The method 300 for providing this data can be used in this case. Figure 1 The method 300 for providing the information is performed using a device or similar equipment. The method includes a reading step 324, a determining step 326, and optionally, an execution step 330.

[0080] In read-in step 324, image data provided by the camera is read from the interface to the camera. The image data represents a camera image of the camera environment. Here, at least one predefined even- and / or odd-point symmetrical region in the environment is arranged in the camera's field of view. From the camera's perspective, at least one predefined even- and / or odd-point symmetrical region may be at least partially occluded by a movable object. Subsequently, in determination step 326, the presence of at least one center of symmetry of at least one even- and / or odd-point symmetrical region in the camera image is determined using the image data and determination rules to determine the occlusion state of the movable object on at least one predefined even- and / or odd-point symmetrical region. Monitoring data is provided based on the determined occlusion state.

[0081] Then, in optional execution step 330, at least one center of symmetry from the camera image is compared with at least one reference center of symmetry from the reference data in terms of intensity, intensity variation over time, and / or local intensity variation to determine an intensity-related deviation between the center of symmetry and the reference center of symmetry. In this case, monitoring data is provided based on this deviation.

[0082] According to one embodiment, the image data read in step 324 represents a camera image of at least one pattern composed of multiple predefined point symmetrical regions. Here, in step 326, the geometric arrangement of the symmetry centers of at least one pattern is determined, a geometric sequence of symmetry types of the symmetry centers is determined, and / or the pattern is determined from multiple predefined patterns using the sequence. This arrangement and / or the sequence represents an identification code for the pattern. Optionally, step 326 and / or step 330 are performed jointly for all symmetry centers regardless of their symmetry type, or individually for symmetry centers of the same symmetry type, depending on their symmetry type.

[0083] Figure 4 A flowchart illustrating an embodiment of a method 400 for detecting movable objects is shown. The method 400 for detection can use... Figure 1 The detection method 400 can be performed using detection equipment or similar equipment. Furthermore, the detection method 400 can be combined with... Figure 3 The method or similar method used for detection is executed. The method 400 for detection includes an evaluation step 444 and an output step 446.

[0084] In evaluation step 444, the evaluation is based on... Figure 3 The monitoring data provided by the method or similar method is used to generate a detection signal that depends on the monitoring data. Subsequently, in output step 446, the detection signal is output to an interface of the processing unit for performing the grating function to perform the detection of the movable object.

[0085] Figure 5 A flowchart illustrating an embodiment of a method 500 for manufacturing is shown. The method 500 can be performed to manufacture at least one predefined point-symmetric region for... Figure 3 The method or similar method used and / or provided Figure 4 The method for detection or a similar method may be used. The method for manufacturing 500 may also be combined with or used in conjunction with... Figure 2 The manufacturing method 500 is performed using equipment or similar equipment used for manufacturing. The manufacturing method 500 includes a generating step 502 and a producing step 506.

[0086] In generation step 502, design data representing a graphical representation of at least one predefined point symmetry region is generated. Subsequently, in generation step 506, the design data is used to generate at least one predefined point symmetry region on, at, or within the display medium to manufacture at least one predefined point symmetry region.

[0087] Figure 6 A schematic diagram of a display medium 600 according to an embodiment is shown, comprising a pattern 610 consisting of predefined point symmetrical regions 110A and 110B. In this case, each predefined point symmetrical region 110A and 110B corresponds to or is similar to... Figure 1 The pattern 610 consists of only 49 predefined point symmetry regions 110A and 110B, as exemplarily shown in Part A of the illustration, and only eight predefined point symmetry regions 110A and 110B, as exemplarily shown in Part B of the illustration. In this case, the first predefined point symmetry region 110A has an odd number of point symmetries as its symmetry type, while the second predefined point symmetry region 110B has an even number of point symmetries as its symmetry type. In this case, a noise-like image pattern having the corresponding pattern 610 is printed on each display medium 600.

[0088] Based on Figure 6 This illustrates the use of symmetry in machine vision according to an embodiment, where symmetry can be designed to be difficult or almost imperceptible to humans, but simultaneously robust to the embodiment, locally accurate, and detectable with minimal computational effort. In this case, point symmetries are more or less hidden in pattern 610, and the observer can hardly identify these point symmetries. Through... Figure 6Predefined dot-symmetric regions 110A and 110B are highlighted graphically, allowing a human observer to identify these regions within a noisy image pattern on the display medium 600. The first part of the illustration A includes 49 exemplary circular dot-symmetric regions 110A and 110B, with only 25 of the first regions 110A having an odd number of dot-symmetries and 24 of the second regions 110B having an even number of dot-symmetries. In the second part of the illustration B, the dot-symmetric regions 110A and 110B are chosen to be larger than those in the first part of the illustration A, with only five of them having an odd number of dot-symmetries and only three of them having an even number of dot-symmetries, thus making them particularly suitable for larger camera distances or lower image resolutions. Therefore, the circular dot-symmetric regions 110A and 110B are positioned on the display medium 600, which is designed as a plate, where, in the case of odd or negative dot-symmetry, a bright dot mirror will appear as a dark image, and vice versa, while in the case of even or positive dot-symmetry, this reversal does not occur. If multiple patterns 610 are required, these patterns can be designed to be distinguishable. This can be accomplished by arranging the symmetrical centers of regions 110A and 110B, such as Figure 6 As shown, the first part of the illustration A and the second part of the illustration B are easily distinguishable, or based on the sequence of negative or odd point symmetry and positive or even point symmetry of regions 110A and 110B within the corresponding pattern 610.

[0089] Figure 7 A schematic diagram of a display medium 600 according to an embodiment is shown, having a pattern 610 composed of predefined point-symmetric regions. The pattern 610 in this case corresponds to or resembles a pattern from... Figure 6 One of the patterns, in which pattern 610 is in Figure 7 It is shown in the illustration but not highlighted graphically. Figure 7 The example shown is only an illustration of the relationship between the two. Figure 6 The display media in the middle are similar to ten display media 600.

[0090] Figure 8 It shows that it has a source Figure 7 A schematic diagram of the display medium 600 with pattern 610, wherein the pattern or predefined point symmetrical regions 110A and 110B are graphically highlighted. By way of example only, the pattern 610 with predefined point symmetrical regions 110A and 110B is arranged or graphically highlighted on ten display media 600 in this case.

[0091] therefore, Figure 7 and Figure 8Ten patterns 610 optimized for distinguishability are shown only as an example. Each pattern 610 has a separate arrangement of odd-point symmetric regions 110A and even-point symmetric regions 110B. The pattern 610 is thus encoded through this arrangement. The encoding is chosen to be mutually coordinated and / or optimized through training so that even if the ten patterns 610 are captured by a camera rotated, mirrored, or partially hidden, these ten patterns remain clearly identifiable and distinguishable. Figure 7 and Figure 8 In pattern 610, the point symmetry regions 110A and 110B at the four corners of each display medium 600 are intentionally designed to be slightly more prominent. This is unrelated to the function itself, but provides practical advantages when manually assembling display media 600 with pattern 610. Display media 600 with pattern 610 can be arranged arbitrarily within the scope of the manufacturing methods already described, such as serially in three dimensions or planarly, or as a surface. Within the scope of the supply methods already described and / or by means of the supply devices already described, the point symmetry center of pattern 610 can be found correctly and accurately. Pattern 610 can, for example, be printed on a solid plate of any size, which can optionally be placed in an arrangement partially orthogonal to each other. Even in the case of blurred imaging of pattern 610 by camera, the symmetry center can be detected sufficiently well to achieve the described function. Therefore, the detection of the point symmetry center is robust for blurred imaging. This expands the application to situations where shallow depth of field is used, such as in low-light scenes, or when the camera's focus or autofocus is incorrectly set or when perfectly sharp images cannot be achieved, such as in liquids, turbid or moving media, in the edge areas of the lens, or during relative movement between pattern 610 and the camera (motion blur, directional blur). Even though point symmetry occurs naturally and especially in artificially designed environments, the potential false detections based on them differ spatially from those based on the correct pattern 610, and therefore the two sets can be easily separated or distinguished from each other.

[0092] To demonstrate that the method described above is also applicable to moving, non-flat, and even elastic surfaces, one can... Figure 7 and Figure 8 The pattern 610 is printed on, for example, paper and assembled into a flexible box. The method described above applies without problem even to non-flat or elastic surfaces (e.g., those made of paper). This makes it possible to determine the movement of these surfaces. Unlike many materials, paper, while not permissible to be cut, exhibits point symmetry that is invariant to shearing, thus shearing poses no problem.

[0093] In particular, the orientation of the center of symmetry in the camera image can be precisely determined. However, extending this precise measurement to the entire surface of pattern 610 may also be of interest in various applications. That is, each point or pixel of pattern 610 indicates where that point or pixel is located in the camera image. This then allows, for example, determining the minimum deviation between the actually observed pattern 610 and the ideal pattern based on the ground truth. For example, it is of interest to apply pattern 610 in a printed manner to a non-smooth or non-rigid surface, thereby creating, for example, variable folds or indentations in pattern 610, the exact shape of which should be determined. Patterns with random characteristics are particularly well-suited for finding corresponding points from a first image to a second image. Here, the first and second images can be recorded chronologically from different perspectives using the same camera or two cameras.

[0094] Specifically, we should now consider a scenario where the first image is a real image from a camera and the second image is an artificially generated (stored) image of a given pattern (also called a reference image), which is placed (e.g., scaled, rotated, affine mapped, projected) onto the second image based on a found center of symmetry, such that it approximates the real (first) image as closely as possible. For the reference image, processing steps required for the first image from the camera, such as image preprocessing, are skipped or omitted if necessary. Known methods, such as optical flow or parallax estimation, can then be applied to find, for example, the corresponding pixel in the reference image for each pixel in the camera image—or vice versa. This results in a two-step process: in the first step, the found center of symmetry, along with any necessary encoding, is used to register or coarsely align the real image with the known pattern. This then represents initialization to precisely determine, in the second step, the minimum deviation in the sense of local displacement between the registered real image and the pattern, again using, for example, optical flow methods, and for each point or pixel of the image or pattern 610, if necessary. The smaller the search area, the less computational effort is required for the second step. The computational workload here is typically very small—due to the good initialization from the first step. Since both steps require very little computation, high pixel throughput is achieved on common computer platforms, defined as the product of the frame repetition rate [images / second] and the image size [pixels / image]. If local inconsistencies are not found, it can usually be explained by the occlusion of an object by the line of sight toward pattern 610. From this, the shape or outline of the occluded object can be inferred.

[0095] A reference image should be provided for the two steps described above. This can be achieved by maintaining an associated reference image for all patterns 610 under discussion in a memory. The resulting memory overhead can be reduced by storing only the relevant parameters needed to recalculate or generate the reference image when required. For example, pattern 610 can be generated according to simple rules using a quasi-random number generator. The term "quasi" here means that the random number generator actually operates according to deterministic rules, so its results are reproducible, which is advantageous here. Here, the rules should be understood, for example, as what diameters the symmetrical regions 110A and 110B have, how mirroring should be performed, and how pattern 610 is composed of multiple patterns with different levels of detail in a weighted manner, such that the pattern is well detectable at short, medium, and long distances. Thus, it is sufficient to store only the initialization data (seed) of the quasi-random number generator and, if necessary, the selection of rules for constructing pattern 610. With the help of this formation rule, the reference pattern can be generated repeatedly and identically when needed (and then deleted again).

[0096] In summary, the two-step process can be represented as follows. In the first step, the centers of symmetry are found and their symbols are determined. Here, the symbols represent the case distinction between odd and even symmetry. By comparing the symbol sequences, it can be determined which of the multiple patterns is involved. The symbol sequence of pattern 610 can also be called a code. This code can be described in a compact way and requires a maximum of 64 bits for pattern 610 with, for example, an 8×8 center of symmetry. For comparison purposes, all existing or considered codes should be stored. From this set, a code that is as consistent as possible with the observation is searched. This result is usually explicit. Even if the camera can only capture a portion of pattern 610, for example, due to occlusion, such a search is still possible because, in this example with an 8×8 center of symmetry, the codes provide a very large number of up to 2 64 This presents several possibilities, but the number of completed patterns 610 will be much smaller, thus providing a high degree of redundancy. For each stored code, information needed to generate a reference image, such as parameter and rule selection, should also be stored. This reference image is generated for the second step, for example, as needed, i.e., only generated when required, and only temporarily if necessary.

[0097] Based on the center of symmetry location found in the camera image coordinates in the first step and its corresponding known location in the reference image, a transformation rule can be calculated to map these coordinates to each other as well as possible, for example, using projection or affine mapping, which is optimized in the sense of least squares. Through this transformation and appropriate filtering of the image data, the two images can be transformed (distorted) into a common coordinate system, such as the coordinate system of the camera image, the coordinate system of the reference image, or any third coordinate system. Then, a more accurate comparison is made between the two images that have thus been aligned, for example, using optical flow methods. For example, for each pixel of the first image (preferably considering its environment), the best corresponding pixel in the second image with the environment is searched. The relative displacement of the corresponding positions can be expressed as displacement information, in particular as absolute coordinates or displacement vectors. Such displacement vectors can be determined with sub-pixel accuracy, so the correspondence is usually not on the pixel grid but between pixel grids. This information allows for highly accurate analysis of the entire surface of pattern 610 captured in a camera image, for example, to analyze the deformation or distortion of pattern 610 or its carrier / display medium 600 using an elastic pattern, or to analyze imaging deviations in the optical path in the case of a rigid pattern.

[0098] If the searched correspondence is not found in the expected area, partial occlusion of pattern 610 can be inferred. The cause of occlusion could be, for example, an object located on pattern 610, or a second pattern that partially occludes the first pattern. Valuable information, such as the mask or outline of an object, can also be obtained from this occlusion analysis.

[0099] Figure 9 A schematic diagram of predefined point-symmetric regions 110A and 110B according to an embodiment is shown. In this case, each predefined point-symmetric region 110A and 110B corresponds to or is similar to a predefined point-symmetric region from one of the above figures. A second point-symmetric or even-numbered point-symmetric region 110B, including its center of symmetry 112, is shown in first part of the illustration A, and a first point-symmetric or odd-numbered point-symmetric region 110A, including its center of symmetry 112, is shown in second part of the illustration B. In this case, the predefined point-symmetric regions 110A and 110B represent regions formed by gray levels.

[0100] The use of point symmetry offers the following advantages over other forms of symmetry: point symmetry is preserved when the pattern and / or at least one predefined point-symmetric region is rotated about the viewing axis; point symmetry is also preserved when the pattern and / or at least one predefined point-symmetric region is tilted, i.e., at a tilted viewpoint. Rotation and tilting of the pattern and / or at least one predefined point-symmetric region do not cause problems for the detection of odd-numbered and even-numbered point symmetry, as both are preserved in the process. Therefore, the methods or approaches already mentioned above are also applicable to tilted viewpoints of the pattern or at least one predefined point-symmetric region. In the case of even-numbered point symmetry, grayscale or color values ​​are preserved, for example, when the points are mirrored.

[0101] and Figure 9 In the first part of the illustration A, at the center of symmetry 112 points, symmetrically, for each gray value g, the same partner gray value g is found. PG =g. In Figure 9 The second part of the illustration, Figure B, shows odd-point symmetry, where each grayscale value is inverted: for example, white becomes black and vice versa, light gray becomes dark gray and vice versa. In the example where the grayscale value g is in the interval 0 ≤ g ≤ 1, from... Figure 9 In the diagram, half of region 110A shown at the top is derived from the original grayscale value g based on g PU =1-g forms the grayscale value g that is mirrored by the point in the simplest possible way. PU Nonlinearity can also be integrated into this inversion, for example, gamma correction, to compensate for other nonlinearities in image display and image recording. The formation of suitable odd- or even-numbered point symmetric patterns is correspondingly straightforward. For example, Figure 9 In the diagram, half of the corresponding area 110A or 110B shown at the top is arbitrarily set or randomly generated. From this, it is then concluded that... Figure 9 The lower half of the diagram is shown, and it is mirrored by points, where the gray values ​​of the odd-numbered points are reversed or the gray values ​​of the even-numbered points are not reversed.

[0102] This observation or generation can also be extended to colored patterns and / or predefined point-symmetric regions. In this case, when the number of points is odd-point symmetric, the RGB values ​​after point mirroring can be formed by inverting the individual original RGB values, which is the simplest possibility, i.e., r PU =1-r (red), g PU =1-g (g represents green here), b PU = 1 - b (blue). Thus, for example, dark violet is imaged as light green, and blue is imaged as orange. A color pattern can represent more information than a monochrome pattern, which can be advantageous. A prerequisite for using this advantage is that color information is also used to convert the raw image (i.e., a color image from a camera or other imaging sensor) into a descriptor.

[0103] The specific implementation of pattern 610 and / or at least one predefined point symmetrical region 110 or 110A and / or 110B should also be discussed below with reference to the above figures.

[0104] Regarding the arrangement of pattern 610 and / or at least one predefined point symmetrical region 110 or 110A and / or 110B, for example, Figure 6 As shown, the point-symmetric regions 110 or 110A and / or 110B can be, for example, circular, and these regions can be mostly arranged in a regular grid in pattern 610. For example, the faces between the circular regions 110 or 110A and / or 110B can remain unused. Alternatives exist: for example, regions 110 or 110A and / or 110B can be square and connected to each other without gaps, thus using an entire face; or the symmetric regions 110 or 110A and / or 110B can be regular hexagonal faces, also connected to each other without gaps, thus using an entire face.

[0105] In this association, Figure 10 A schematic diagram of a pattern 610, comprising predefined point symmetric regions 110A and 110B according to an embodiment, is shown. The predefined point symmetric regions 110A and 110B in this case correspond to or resemble... Figure 1 , Figure 6 and / or Figure 8 The symmetric region of the predefined points in the [reference]. Figure 10 Regions 110A and 110B in pattern 610 are both circular and arranged on a hexagonal grid. In this case, the distance between grid points or centers of symmetry can correspond to the diameter of the circle. Thus, the unused surface 1010 between regions 110A and 110B in pattern 610 can be minimized.

[0106] Other arrangements and shapes, such as rectangles, polygons, etc., are also possible, and they can be combined with each other in shape and / or size. For example, alternations of pentagons and hexagons, like a regular soccer ball. Shapes can also be arranged in other ways, such as rotation, with asymmetrical regions where necessary. The center of symmetry can also be located outside the point-symmetric region itself. This is the case, for example, when a torus is used as a shape. It is also not necessary for all point-symmetric regions to lie in a common plane. Instead, they can lie on different faces arranged in space, and these faces are also allowed to be non-flat.

[0107] Pattern 610 and / or at least one predefined point symmetrical region 110 or 110A and / or 110B can be formed in a variety of ways. Only a few examples are illustrated below. Random or quasi-random patterns, such as noise patterns. By introducing low spatial frequency components, these patterns are formed such that they are perceived as noise patterns with sufficiently high contrast even at moderate to large distances from the camera. So-called white noise, i.e., uncorrelated grayscale values, is not suitable for this purpose. Aesthetically pleasing, and where necessary, regular patterns, such as floral patterns, tendril patterns (leaves, branches, flowers), decorative patterns, mosaics, mathematical patterns, traditional patterns, onion patterns, patterns composed of iconic symbols (hearts, etc.), imitations of random patterns in nature (e.g., farmland, woodland, lawns, pebble beaches, sand, bulk materials (gravel, salt, rice, seeds), marble, rubble, concrete, brick, slate, asphalt surfaces, starry skies, water surfaces, felt, hammered paint, rusted iron sheets, sheepskin, scattered particles, etc.), and scene photographs with any content. To generate point-symmetric regions and / or patterns from this pattern suitable for the purposes described herein, half of the corresponding face is arbitrarily pre-given, and a second half is constructed by point mirroring, with grayscale or color values ​​inverted if necessary. See also [link to relevant documentation]. Figure 9 As a simple example.

[0108] There are countless possibilities regarding the material, surface, and manufacture of pattern 610 and / or at least one predefined point symmetrical region 110 or 110A and / or 110B. The following list is not exhaustive: black and white printing, grayscale printing, or multicolor printing on various materials; printing on or behind glass or transparent films; printing on or behind frosted glass or translucent films; relief in stone, glass, plastic, or rubber; relief in fired materials such as pottery, terracotta, or ceramics; relief casting in metal, concrete, or plaster; embossing on plastic or paper / cardboard; etching on glass, metal, or ceramic surfaces; milling in wood, cardboard, metal, stone, etc.; fired surfaces in wood or paper; photographic exposure of paper or other materials; temporary or decaying or water-soluble patterns for short-term applications on plant materials, ash, sand, wood, paper, fruit, food peels, etc.; displays as holograms; displays on monitors or displays (which may vary over time if necessary); displays on LCD films or other display films (which may vary over time if necessary), etc.

[0109] Regarding the possibilities of relief manufacturing, such as milling, embossing, stamping, etc., it should be noted that the area should be perceived by the camera as having odd and / or even point symmetry. Therefore, it may be necessary to consider, for example, later lighting (e.g., light incident obliquely on the relief) and nonlinearities and other disturbances in optical imaging during the design phase. Whether the 3D shape or relief itself has an even and / or odd point symmetry type is not important; rather, it is the image recorded by the camera that shows this symmetry. Here, the direction of light incident or illumination and the reflection of light on the surface are also relevant and should be considered together in the design. Regarding image recording and lighting, it should be noted that the recording technology should be designed to be suitable for capturing pattern 610 and / or at least one predefined point symmetry region 110 or 110A and / or 110B. In particular, in cases of rapid relative movement between pattern 610 and / or (one or more) areas 110 or 110A and / or 110B and the camera, it is recommended to use appropriate lighting (e.g., flashlight, strobe light, or bright LED light) to minimize exposure time and motion blur in the resulting image. For various applications, it is meaningful to apply pattern 610 and / or (one or more) areas 110 or 110A and / or 110B to a transparent or translucent surface. This allows pattern 610 and / or (one or more) areas 110 or 110A and / or 110B to be illuminated from one side and observed from the other. This solution effectively avoids interfering reflections of the light source on the display medium. In principle, there is freedom to choose the front or back of the carrier or display medium for the arrangement of pattern 610 and / or (one or more) areas 110 or 110A and / or 110B, the light source, and the camera. When selected, the risk of pattern 610 and / or (one or more) areas 110 or 110A and / or 110B or the camera being contaminated or pattern 610 and / or (one or more) areas 110 or 110A and / or 110B being worn can also come into play: thus, for example, it makes sense to apply pattern 610 and / or (one or more) areas 110 or 110A and / or 110B and the camera to the back, because they are better protected there from, for example, dust or water, or because pattern 610 and / or (one or more) areas 110 or 110A and / or 110B are protected there from mechanical wear.

[0110] A method, also used in embodiments, is disclosed in DE 10 2020 202 160, which is published later, to reliably and with minimal computational effort find symmetrical regions or patterns in an image. In this case, the original image, i.e., a color or grayscale image from a camera or other imaging sensor, is converted into an image of descriptors, wherein the descriptors are formed based on the local environment of the original image. Here, a descriptor is another representative form of the local image content, prepared in a form that is easier to process. More simply here, it is understood in particular to include information about the environment of a point, not just about the point itself, a high degree of invariance to brightness or illumination and its variations, and low sensitivity to sensor noise. The descriptor image can have the same resolution as the original image, such that approximately one descriptor exists for each pixel of the original image. Alternatively or additionally, other resolutions are also possible.

[0111] A signature is formed from a corresponding descriptor, represented as a binary word in a computer unit, or from multiple adjacent descriptors. The signature describes the local environment of the pixels in the original image as characteristically as possible. The signature can also be the same as a descriptor or a portion thereof. The signature is used as an address to access a lookup table. Therefore, if the signature consists of N bits, it can access a lookup table of size 2. N A lookup table (i.e., 2 to the power of N). Advantageously, the word length N of the signature should not be chosen too large, as the storage requirements of the table grow exponentially with N: for example, 8 ≤ N ≤ 32. The signature or descriptor is constructed such that the signature symmetry can be determined using simple operations, such as a bitwise XOR operation on a subset of bits. Example: S P =s^R P Where s is a signature of length N, R P It is a point-symmetric (P) and its corresponding reflector (R). The symbol ^ represents the bitwise XOR operation. Therefore, the signature S P The point-symmetric counterpart of the signature 's'. This relationship also applies to the opposite direction.

[0112] If the construction of the descriptor or signature is fixed, the reflector is therefore automatically set (and constant). By applying it to any signature, that signature can be converted into its symmetric counterpart. An algorithm exists that can find one or more symmetric signature pixels for a given signature at the current pixel within an optional finite search window. The center of symmetry is then located in the middle of the line connecting the positions of these two pixels. Voting weights are output there or as close as possible and collected in a voting map. In the voting map, the output voting weights accumulate at the locations of the searched centers of symmetry. These centers of symmetry can thus be found, for example, by traversing the voting map to find the accumulation points. This works for point symmetry, horizontal axis symmetry, vertical axis symmetry, and other symmetries where needed, such as mirror symmetry on other axes, and rotational symmetry. More precise localization with sub-pixel accuracy can be achieved if the local environment is also included in the observation when evaluating the voting matrix to determine the accumulation points and precisely locating the centers of symmetry.

[0113] DE 102020202160 Figure 15 An algorithm is presented that can find point-symmetric correspondences with the currently observed signature. However, this paper only considers even-numbered point symmetries.

[0114] According to an embodiment, the algorithm is extended to odd-point symmetry. Particularly advantageous here is that odd-point and even-point symmetries can be determined simultaneously in a single common traversal. This saves time, as only one traversal of the signature image is needed instead of two, and reduces latency. When only one (instead of two) traversal is required, the streaming mode processing can provide the results of the symmetry search with significantly lower latency. Here, processing begins as soon as the first pixel data from the camera arrives, and the processing steps are executed intensively and sequentially. This means that the signature is computed as soon as the necessary image data from the local environment of the current pixel is available. A symmetry search is immediately performed on the newly formed signature. Once some parts of the voting matrix are complete (as is the case when these parts are no longer and will no longer be part of the search area), these parts can be evaluated immediately, and the found symmetry (strong symmetry center) can be output immediately. This process results in very low latency, typically corresponding to only a small number of image rows, depending on the height of the search area. Low latency is crucial if a rapid response is required, such as within an adjustment loop where the actuator influences the relative pose between the symmetric object and the camera. Memory is also saved. The voting map can be used for both even-point and odd-point symmetry forms, where the two symmetry forms or types with different signs participate in the voting. For example, the voting weight is subtracted for odd-point symmetry and added for even-point symmetry. This will be explained in more detail below. Furthermore, energy can be saved by conserving memory. The aforementioned low-latency implementation also results in only a small amount of intermediate data needing to be stored compared to the entire image. This memory-efficient operation is particularly important for cost-critical embedded systems and also leads to savings in energy requirements.

[0115] Figure 11 A schematic diagram illustrating the use of lookup table 1150 according to an embodiment is shown. Lookup table 1150 can be generated by... Figure 1 The specific means by which the equipment or similar equipment is provided is used. In other words, Figure 11 An example of the algorithm process for finding symmetric correspondences at search points is as follows: Figure 1 The equipment or similar equipment used for provision and / or Figure 3 A snapshot related to the method or similar method being provided. Specifically, Figure 11 The illustration in the document is also similar to that in the later published DE 10 2020 202 160. Figure 15 , among which here Figure 11 It also includes extensions to include even-point symmetry and odd-point symmetry.

[0116] Lookup table 1150, also known as an entry table, is shown. A pixel grid 1100 is illustrated, in which signatures with exemplary values ​​2412 are generated for the currently observed or processed pixel. In other words, Figure 11 A snapshot is shown during the formation of links of pixels or pixel coordinates with the same signature s. For clarity, two of at most N possible chains are shown, and this is for signature S. PG =364 and for signature S PU =3731. In pixel grid 1100, a reference to the position of the last previously signed image with the same signature value is stored for each pixel. This generates links to positions with the same signature. Therefore, the signature value itself does not need to be stored. For each signature value, the corresponding entry position in pixel grid 1100 is stored in a lookup table 1150 or an entry table with N table fields. Here, N corresponds to the number of possible signature values. The stored value can also be "invalid". The contents of lookup table 1150 or the entry table and the referenced images (linked images) change dynamically.

[0117] In pixel grid 1100, pixels are processed row by row, for example from... Figure 11 Starting from the top left, as indicated by the arrow, and having currently progressed to the pixel with signature s = 2412. Links between pixel positions having the same signature s are stored only for the first image region 1101. For the second image region 1102 in the lower image portion, links and signatures are not yet known at the indicated time point, and for the third image region 1103 in the upper image portion, links are no longer needed, for example, due to the limitations of the search area, where the link memory for pixels in the third image region 1103 can be freed again.

[0118] For the newly formed signature s, by applying reflector R PG Form an even-numbered point mirror signature S PG =364. Index PG represents point-symmetric, even. Index PU, representing point-symmetric, odd, is also used below. This value is used as the address in lookup table 1150 to find the address assigned to the same signature value S. PG The entry is found in the link at pixel position 364. At the indicated time point, lookup table 1150 includes two elements: the entry pixel position corresponding to signature s and a reference to that position indicated by the curved arrow. For clarity, other possible contents of lookup table 1150 are not shown. Signature value S PGThe link = 364 includes three pixel positions, only shown here as an example. Two of these are located within search region 1104, which can also have a different form than shown here, such as a rectangle or a circle. Here, when traversing unidirectionally along the link, starting from the bottom, two symmetrical corresponding candidates for the two points located within search region 1104 are found. The third correspondence as the first element of the link symmetrical to the even-numbered point is not of interest here, as it is located outside search region 1104 and therefore too far from the current pixel position. If the number of symmetrical center candidates 1112 is not too large, the voting weight of the corresponding symmetrical center position can be output for each symmetrical center candidate 1112. The symmetrical center candidates 1112 are located at the positions of signatures s and the corresponding even-numbered point mirror images of signatures S, respectively. PG The middle of the connecting axis between them. If there is more than one candidate symmetry center 1112, the voting weight can be reduced respectively, for example, the reciprocal of the number of candidate symmetry centers can be used as the corresponding voting weight. Thus, the unclear candidate symmetry center is weighted less than the clear candidate symmetry center.

[0119] We will now consider and use odd-point mirror signatures. Figure 11 In the snapshot shown, the newly formed signature s is processed by applying another reflector R. PU Form an odd-numbered point mirror signature S PU =3731. Similar to the process described above for mirror signatures of even-numbered points, the same steps are performed for mirror signatures of odd-numbered points. The entry for the corresponding link is found using the same lookup table 1150. Here, lookup table 1150 points to the link symmetrically represented for signature 3731 at odd-numbered points. The first two pixel positions along this link again lead to the formation of symmetry center candidates 1112, as they are arranged in search area 1104 and because the number of candidate symmetry center candidates 1112 is not too large. The last pixel position along this link is located in the third image area 1103. This area is no longer needed because it can no longer enter the search area 1104 that slides line by line here.

[0120] If the next reference within the link points to the third image region 1103, traversal along the link can be terminated. Of course, traversal also terminates when the end of the link is reached. In both cases, it makes sense to limit the number of symmetry center candidates 1112; that is, if there are too many competing symmetry center candidates 1112, all symmetry center candidates 1112 are discarded. Furthermore, it makes sense to terminate traversal along the link early if neither its end nor the third image region 1103 can be reached after a pre-given maximum number of steps along the link. In this case, all symmetry center candidates 1112 found up to there should also be discarded.

[0121] The memory used for links in the third image region 1103 can be freed up again, so only the link memory needs to be reserved for the size of the first image region 1101. Therefore, the link memory requirement is generally low and here depends essentially only on one dimension of the search region 1104 (here, the search region height) and one dimension of the signature image (here, the signature image width).

[0122] The candidate for symmetry center 1112 or the candidate for symmetry center may not always fall exactly at the pixel location; instead, there are three other possibilities. Therefore, there are a total of four possibilities:

[0123] 1. The point or center of symmetry candidate 1112 falls on the pixel position.

[0124] 2. The point or symmetry center candidate 1112 falls in the middle between two horizontally directly adjacent pixel positions.

[0125] 3. The point or symmetry center candidate 1112 falls in the middle between two vertically directly adjacent pixel positions.

[0126] 4. The point or symmetry center candidate 1112 falls in the middle between four directly adjacent pixel positions.

[0127] In cases 2 through 4 where the details are unclear, it is advantageous to distribute the voting weights to be output evenly across the participating pixel locations. The output voting weights are then input into the voting matrix and summed or accumulated therein.

[0128] Here, not only positive voting weights but also negative voting weights are used simultaneously. Specifically, even-numbered symmetry is equipped with a different sign (positive) than odd-numbered symmetry (negative here). This leads to a clear result: in image regions without symmetry, which in practice largely represent the majority, the positive and negative voting weight outputs are approximately balanced, thus roughly canceling each other out in the voting matrix. Therefore, on average, approximately zero is obtained in the voting matrix. Conversely, in either odd-numbered or even-numbered symmetric regions, strong extrema are obtained in the voting matrix, and in this embodiment, a negative minimum is obtained when symmetric at odd points, and a positive maximum is obtained when symmetric at even points.

[0129] According to the embodiment shown here, the same resources are used for both odd-point symmetry and even-point symmetry, namely lookup table 1150 or entry table, link graph, voting matrix, which in particular saves memory requirements, and both symmetry forms or types are observed in a single common traversal, which saves time and intermediate memory.

[0130] Figure 12 A schematic diagram of a voting matrix according to an embodiment is shown in Table 1200. Table 1200 relates to a voting matrix, as a means of... Figure 1 A 3D image of a camera image processed by a provided device or similar device, in which the camera recorded from... Figure 6 The second part of the illustration shows the pattern. In the voting matrix or chart 1200, the exemplary three maximum values ​​1210B and five minimum values ​​1210A can be clearly identified, representing those from... Figure 6 The second part of the illustration shows the symmetrical regions of three even-numbered points and five odd-numbered points. Outside of these extreme values, the values ​​in the voting matrix are close to zero. Therefore, the extreme values ​​can be determined very easily, and the location of the center of symmetry in the camera image can be determined explicitly and precisely.

[0131] Figure 12 These extreme values ​​are shown to be very obvious and therefore can be obtained through Figure 1 The equipment or similar equipment used for provision and / or Figure 3 The method or similar method used to provide this information is simple and unambiguous in detecting the symmetry. Here, information about the type of symmetry (i.e., odd or even) is included in the symbols. If the local environment of the corresponding extrema is also considered when evaluating the voting matrix, the location of the symmetry center can be determined with high precision at sub-pixel accuracy. Corresponding methods for this purpose are known to those skilled in the art. If the pattern is constructed appropriately, odd-point symmetry and even-point symmetry will not compete with each other. Thus, image regions (if any) will either have odd-point symmetry or even-point symmetry. Even if odd-point symmetric regions and even-point symmetric regions are close to each other in the camera image, it can be ensured that their symmetry centers remain spatially separated or distinguishable. Then, by jointly processing negative and positive symmetry, advantages in terms of resources and speed are achieved.

[0132] According to an embodiment, the processing of odd-point symmetry and even-point symmetry can be set up separately. Separating them before inputting entries into the voting matrix makes sense: two unsigned voting matrices are then set up to replace the common signed voting matrix, where the voting weights for negative symmetry are input into the first voting matrix and the voting weights for positive symmetry are input into the second voting matrix. This presents a potentially interesting advantage: a pattern can also be constructed and considered by the detection algorithm, which simultaneously exhibits odd-point symmetry and even-point symmetry with their centers of symmetry locally coinciding. While this mixed form of symmetry is highly unusual, this unusualness guarantees that it is extremely unlikely to be confused with randomly occurring patterns in the image. The two voting matrices are then searched to find the maximum value present at the same location in both matrices. Another possible advantage of processing odd-point symmetry and even-point symmetry separately is that it is easier to parallelize, thereby enabling faster execution when necessary. Because by using two voting matrices, access conflicts during voting weight input can be avoided, saving waiting time.

[0133] Figure 13 A schematic diagram of pattern 610, which is arranged in a cubic form according to an embodiment, is shown in terms of the correct identification of grid 1311. Figure 13 The pattern 610 shown is, for example, from Figure 7 or Figure 8 The pattern, in which three patterns are arranged in a cubic shape. In pattern 610, the detected or identified centers of symmetry 112A and 112B of the corresponding predefined point symmetry regions of pattern 610 are shown, wherein the signs and values ​​of the associated extrema in the voting matrix can optionally also be known. In this case, the first center of symmetry 112A is assigned to the predefined point symmetry region with odd-numbered point symmetry, and the second center of symmetry 112b is assigned to the predefined point symmetry region with even-numbered point symmetry. A correct grid 1311 is drawn for one of the patterns 610, on which the predefined point symmetry regions and thus the centers of symmetry 112A and 112B are aligned. For the other two patterns 610, the correct grid is searched, wherein in Figure 13 In the diagram, an incorrect solution to the grid search is indicated by the first label 1313, and a correct solution to the grid search is indicated by the second label 1314.

[0134] Finding the correct associated grid is a task with inherent fuzziness. After detecting the odd / even coded centers of symmetry 112A and 112B, the next step is typically to group them and determine which pattern 610 this group is assigned to, since it is not always known beforehand which patterns 610 and how many patterns 610 are included in the image. Part of this task could be finding the grid 1311 on which the centers of symmetry 112A and 112B are arranged. Instead of the square grid 1311, other topologies for arranging the centers of symmetry 112A and 112B are also considered, such as a concentric annular arrangement, see, for example... Figure 6 The second part of the illustration. As a representative example, observe square grid 1311 below.

[0135] Based on only Figure 13 The task of determining the correct grid positions for all patterns 610 by identifying the symmetry centers 112A and 112B is, in some cases, an ambiguous problem. If in Figure 13Observing pattern 610, if the correct grid 1311 has already been drawn for this pattern, it is not difficult to indicate the correct grid 1311 (to the observer). However, for the other two patterns 610 captured by the camera from a significantly more oblique perspective, it is clear that the output may be ambiguous. There are several possible solutions regarding how the grid can be placed through the centers of symmetry 112A and 112B. Here, the solution that is initially most obvious when viewed locally, i.e., the solution with an approximately vertical axis, is not the correct solution, as can be seen based on the first mark 1313. Instead, the second mark 1314 is correctly located on the grid. This shows that a naive process, such as searching for the nearest neighbor of the corresponding center of symmetry, may lead to an incorrect solution when viewed from an oblique perspective. In practice, solutions with a very oblique perspective are excluded because it is no longer possible to find the centers of symmetry 112A and 112B.

[0136] Figure 14 Shown from a tilted perspective Figure 6 The first part of the illustration shows a schematic diagram of pattern 610. Figure 14 The image shows a display medium 600 having a pattern 610 consisting of predefined point symmetrical regions 110A and 110B. Figure 14 The second part of the diagram, Figure B, shows the method of using... Figure 1 The equipment or similar equipment used for provision and / or Figure 3 The center of symmetry 112A and 112B of pattern 610 are used to identify or detect the pattern using the provided method or similar method. The center of symmetry 112A and 112B have been detected and at least their positions are available.

[0137] Figure 15 Showing from Figure 14 The first part of the illustration depicts pattern 610, in which predefined point symmetrical regions 110B are highlighted. Here, the predefined even-numbered point symmetrical regions 110B are highlighted graphically only as an example to illustrate the distortion of pattern 610 or regions 110A and 110B due to a tilted perspective. Here, the exemplary circular predefined point symmetrical regions 110A and 110B are distorted into ellipses by the tilted perspective.

[0138] The following is a special reference Figure 14 and Figure 15 Furthermore, the reconstruction of the correct mesh or topology of pattern 610 is discussed in general with reference to the above-mentioned figures.

[0139] From an oblique perspective, each circular region 110A and 110B from which the voting for the corresponding centers of symmetry 112A and 112B originates becomes an ellipse. This is achieved by backtracking on the corresponding centers of symmetry 112A and 112B (e.g., ...). Figure 15The voting, which contributes to the highlighted even-point symmetry center 112B, allows us to infer the shape and orientation of the corresponding ellipse. The direction and ratio of the ellipse's principal axis reveal how the ellipse can be stretched or straightened to transform it back into a circle. Observe the exemplary highlighted predefined even-point symmetry region 110B of pattern 610, which contributes to the highlighted point symmetry center 112B. Depending on the design or construction, this region 110B is circular or approximately circular, such as hexagonal. At an oblique viewpoint, this circle becomes an ellipse. When voting is conducted to identify the symmetry center 112B, pairs of symmetric points help to form extrema in the voting matrix located within this ellipse.

[0140] According to one embodiment, the origin of point pairs in the camera image that lead to the formation of sufficiently strong extrema is traced. Further processing steps are performed for this purpose. First, it is assumed that voting has been conducted and a sufficiently strong center of symmetry has been found. Therefore, the starting point is as follows: Figure 14 The second part of the diagram illustrates the situation shown in Figure B. The voting process is then iterated again in a modified form. However, the existing voting matrix is ​​not reformulated here. Instead, for each pair of symmetric points that contributes to the voting matrix, it is checked whether that contribution contributes to one of the found symmetry centers 112A and 112B, and therefore has already been contributed to in the first iteration. If so, the two positions of that pair are stored or immediately further calculated. Advantageously, the indices of the symmetry centers 112A and 112B contributed by the symmetric point pair are also stored or used here. In this way, all contributions to the successful symmetry centers can be determined afterward and (intermediately) stored or further used.

[0141] The further processing steps do not necessarily begin after the completion of the first processing step, namely the formation of the voting matrix and the determination of the centers of symmetry. Instead, they can begin earlier and utilize the intermediate results already completed in the first processing step, namely the found centers of symmetry 112A and 112B. Then, from the information formed in this way, all image locations contributing to each found center of symmetry 112A and 112B can be read out. These locations are substantially, or except for a few outliers, located within the ellipse, such as... Figure 15 The example shown is with respect to the center of symmetry 112B.

[0142] Methods for determining the parameters of the ellipse are known to those skilled in the art. For example, a principal axis transformation can be formed over the set of all points contributing to the centers of symmetry 112A, 112B to determine the orientation of the principal axes and the two diameters of the ellipse. This can be achieved even without the need for intermediate storage of contributing image locations: instead, these image locations can be further processed immediately upon being known. Alternatively, an elliptical envelope can be determined around the set of points, using this elliptical envelope to enclose as closely as possible the largest possible portion of the set of points (excluding possible outliers).

[0143] Alternatively, an index image, equivalent to an index matrix, can be created instead of a list of points. The index image serves the same purpose—forming the parameters of all ellipses—but stores information in a different form. Ideally, the index image has the same dimensions as the signature image and is set to store indices, specifically those assigned to the found centers of symmetry 112A and 112B. Special index values, such as 0, are set to indicate that no entry exists yet. If a pair of symmetric points or signatures contributing to the i-th index is found during further processing steps, index i is entered at the two associated positions of the corresponding signature. Thus, at the end of the traversal, the following index image is obtained, in which all indices assigned to the centers of symmetry 112A and 112B appear multiple times, forming elliptical regions: thus, apart from a few outliers, each elliptical region contains only entries with uniform indices, and index 0 at unused positions. The index image can then be easily evaluated to determine the parameters of the individual ellipses. Furthermore, it is not necessary to store the entire index image. Once the data in a segment of the indexed image stops changing, that segment can be evaluated, and the memory can be freed up again. This results in lower latency, allowing intermediate results to be provided earlier.

[0144] The known elliptic parameters can then be used to correct the two-dimensional arrangement of the detected centers of symmetry (see...). Figure 14 This allows these centers of symmetry to subsequently lie on the grid of pattern 610, which here is at least approximately square, for example only.

[0145] Figure 16 The image after viewpoint correction is shown according to an embodiment. Figure 15 A schematic diagram of pattern 610. In other words, for illustrative purposes, Figure 16 It shows that in the Figure 15 Pattern 610 is orthogonal to or perpendicular to the direction of the found ellipse or the highlighted elliptical twisted region 110B, stretched by the ratio of the two principal axis lengths. Therefore, the correct grid 1311 can be found in a simple way. Thus, with... Figure 15In contrast, the ellipse is corrected by restoring the original circular shape of region 110B. Then, determining the grid 1311 where the centers of symmetry 112A and 112B are located, or determining the adjacency relationship between the centers of symmetry 112A and 112B without errors, is a straightforward matter. Figure 16 This is for illustrative purposes only. In practice, there is no need to distort the image. Since the information about the positions of the centers of symmetry 112A and 112B already exists in compressed form, it makes sense to use only this data for further processing and to transform its coordinates, where the transformation rule is formed by the determined ellipse parameters, and makes the ellipse into a circle.

[0146] When recording camera images at a telephoto focal length, a single global transformation is sufficient to determine grid 1311 for each segment. When recording camera images using a wide-angle lens (e.g., a fisheye lens), local transformations can be used at least in some areas. Therefore, the transformation rules described above can be applied globally and / or locally. In the global transformation, all projection centers are transformed using the same common transformation rule. This is meaningful and sufficient in many cases. The common transformation rule can be formed based on the common observation of all ellipses. If the centers of symmetry 112A and 112B lie on multiple planes in space, the ellipses can be grouped according to their parameters. Here, ellipses belonging to a plane have very similar parameters—especially when the plane is flat. A global transformation rule can then be determined and applied for each group. This process is applicable to telephoto focal lengths. Local transformations are meaningful when multiple circular regions are imaged as ellipses of different shapes or orientations by camera imaging. This is especially true for wide-angle cameras or high-torque lenses.

[0147] After the transformation is applied, the centers of symmetry belonging to the same face are at least approximately located on a common grid 1311. The next task is to assign the centers of symmetry 112A and 112B to grid locations. This can be done, for example, iteratively in small steps. For example, for centers of symmetry 112A and 112B, search for up to four nearest neighbors with approximately the same distance, for which see also [link to documentation]. Figure 13The search continues from these neighbors to more distant neighbors until all captured centers of symmetry 112A and 112B belonging to pattern 610 are assigned to a common grid 1311 or can be excluded from the common grid 1311. Therefore, if a center of symmetry is encountered during this search that does not match the grid 1311 just observed in terms of distance, these centers of symmetry are not recorded, as they may be outliers or centers of symmetry belonging to other faces. This iterative search can be repeated for other faces, such that eventually every center of symmetry 112A, 112B, except for outliers, is assigned to a face. For these faces, pattern 610 can then be identified preferably based on the binary codes associated with the centers of symmetry 112A and 112B, which are respectively contained in the symbols of the extrema.

[0148] Figure 17 A schematic diagram of an embodiment of a pattern 1710 with layered symmetry is shown. Pattern 1710 corresponds to or is similar to the pattern in the above figures. More specifically, by way of example only, pattern 1710 has a two-level layered structure consisting of four predefined point-symmetric regions 110A and 110B. According to the embodiment shown here, by way of example only, pattern 1710 has two predefined odd-point-symmetric regions 110A and two predefined even-point-symmetric regions 110B. In this case, pattern 1710 has an odd-point-symmetric structure overall. The even-point-symmetric regions 110B and the odd-point-symmetric regions 110A are located at the first layered level. The overall arrangement of the odd-point-symmetric pattern 110B is located at the second layered level. The center of symmetry 112 of the second layered level is represented by a quarter circle.

[0149] Figure 18 A schematic diagram of an embodiment of pattern 1810 with layered symmetry is shown. Figure 18 The pattern 1810 in the image is similar to that from Figure 17 The pattern. More precisely, Figure 18 Another example of a two-level hierarchical structure consisting of predefined point-symmetric regions 110B is shown. In the first hierarchical level, the predefined point-symmetric regions 110B are assumed to be point-symmetric themselves. In the second hierarchical level, there is an odd-numbered point symmetry at the level of pattern 1810, where the center of symmetry 112 is located at the center of the six-part hexagon shown for illustration. This odd-numbered symmetry is represented here as a reversal of the predefined point-symmetric regions 110B, for example, mirroring a dark symbol on a light background as a light symbol on a dark background.

[0150] Figure 19 A schematic diagram of an embodiment with a layered symmetrical pattern 610 is shown. In this case, pattern 610 is composed of... Figure 17 and Figure 18Patterns 1710 and 1810, or their inversions and / or dotted mirror forms, are constructed. For example only, pattern 610 has... Figure 17 The two patterns 1710 and Figure 18 The three-tiered structure consists of two patterns 1810. Patterns 1710 and 1810 are odd in number, and therefore are mirrored at the center of symmetry 112 of pattern 610, which is located at the center of the six-part hexagon shown for illustration. For example, Figure 19 The pattern 1710 shown in the lower right corner is the reverse of the pattern 1710 in the upper left corner. This layering principle can be continued at will, that is, a fourth level, a fifth level, and so on can be constructed.

[0151] The following is for reference. Figure 17 , Figure 18 and Figure 19 Further discussion is given of patterns with hierarchical symmetry. Symmetrical patterns 610, 1710, and 1810 can be constructed in multiple levels such that, for example, there are small self-symmetrical regions in the first hierarchical level, and common observation of them leads to symmetry in the next higher hierarchical level. Figure 17 and Figure 18 Both examples exemplify how to construct two-level layered patterns 1710 or 1810. Based on this, in Figure 19 A three-level layered pattern 610 was constructed. Therefore, in Figure 19The example includes three hierarchical levels. The third hierarchical level extends across the entire surface of pattern 610 (the area enclosed by dashed lines) and includes a center of symmetry 112. In the second hierarchical level, there are four patterns 1710 and 1810 (each enclosed by solid lines), each with a central center of symmetry (not explicitly shown here). According to the embodiment shown here, there are therefore 16 predefined point symmetric regions in the first hierarchical level, each with a center of symmetry. Here, the symmetry of the third hierarchical level is visible from a greater distance. During close proximity, the four symmetries of the second hierarchical level are also visible. At shorter distances, or if the capture resolution of pattern 610 is sufficient, the symmetry of the first hierarchical level also becomes visible. Therefore, visual servoing, such as visual control of a robot in the direction of pattern 610 or in any other direction, can be implemented over a large range of distances. If finer or lower hierarchical levels can already be captured, it is generally unnecessary to capture coarser or higher hierarchical levels. It is also unnecessary to capture all symmetries at the corresponding hierarchical level simultaneously; for example, at very short distances, it is simply impossible to capture the entire pattern 610 in a camera image. Clearly, even and odd symmetries can be chosen and combined with some degree of freedom. Additional information can also be included in this setting, specifically a bit allocated for the choice between odd and even symmetries, which can be transmitted to the capture system in this way. "Some degree of freedom" here means that the remaining form of the symmetry at the corresponding hierarchical level inevitably derives from the next higher hierarchical level. In other words, for example, in… Figure 18 In the middle, for the top row, the patterns "X" and "O" can be freely chosen. Then, the second row is inevitably derived, and here it is reversed because negative point symmetry was chosen on the next layer level.

[0152] Figure 20 A schematic diagram of pattern 610 according to an embodiment is shown. In the first part of the illustration A, Figure 20 Pattern 610 is shown as an example; pattern 610 is from... Figure 8 One of the patterns. Figure 20 The first part, illustration A, is an example of implicit additional information, 8.8 = 64 bits, derived here for illustrative purposes only, based on the symmetry type of predefined point-symmetric regions 110A and 110B of pattern 610, or the symbol of the associated point symmetry. In the second part, illustration B, Figure 20Pattern 610 is shown, which is constructed, by way of example, from four predefined point-symmetric regions 110A and 110B. For example, it is constructed from one predefined odd-point-symmetric region 110A and three predefined even-point-symmetric regions 110B on a square grid. Furthermore, in this case, a code matrix 2010 for explicit additional information is arranged in pattern 610. By way of example only, the implicit additional information from the first part of the illustration A is explicitly contained in the code matrix 2010. The predefined region 110A with odd-point symmetry here represents or marks the starting row of the 8×8 matrix, thereby explicitly setting the readout order.

[0153] The following is for reference. Figure 20 The delivery of implicit or explicit additional information will be discussed in more detail.

[0154] It may be useful or necessary to transmit additional information to a recipient, such as a computer, autonomous robot, etc., based on pattern 610. The additional information can be more or less extensive. Some illustrative examples of additional information include parking spots, charging stations, southwest-facing locations at 52°07′01.9″N 9°53′57.4″E, left turns, speed limits of 20 km / h, lawnmower charging stations, etc. Various options exist for transmitting information using imaging sensors or cameras. In particular, a distinction can be made between implicitly included and explicitly included additional information; for this, see [reference needed]. Figure 20 The two examples illustrate this, one implicitly and one explicitly, providing 64 bits of additional information. Implicit additional information means that it is somehow contained within the pattern 610 itself, which is symmetrical, while explicit additional information is typically designed and captured separately from these patterns 610.

[0155] based on Figure 20 The first part of the diagram, Figure A, illustrates one possibility for transmitting implicit additional information: implicit additional information as binary code. Since the choice between odd-point symmetry and even-point symmetry is made for each symmetric region 110A and 110B when constructing pattern 610, additional binary information (corresponding to 1 bit) can be transmitted separately. If patterns with both odd and even-point symmetry are also allowed simultaneously, then the binary additional information becomes ternary additional information, i.e., three cases instead of two.

[0156] Another possibility for transmitting additional information is derived by using the non-uniform distance between the centers of symmetry of regions 110A and 110B, i.e., implicit additional information based on this arrangement. Then, with... Figure 20 The arrangements shown are different—in Figure 20The centers of symmetry are located on a square grid, and these centers of symmetry will be arranged irregularly, with additional information or a portion thereof encoded in this arrangement. Example: If the corresponding centers of symmetry are allowed to shift a fixed distance to the left / right and up / down, nine possible positions are obtained, whereby each center of symmetry can encode log2(9) = 3.17 bits of additional information. The tilt angle between the imaging sensor and pattern 610 does not pose a problem in any of the possibilities mentioned. For example, a subset of the centers of symmetry (e.g., the four outermost centers of symmetry in the corners) can be used to define the base grid of the coordinate system or rules. The deviation or binary / ternary code used for encoding is then related to this base grid.

[0157] The symmetric regions 110A and 110B used for implicit additional information should not be too small, so as to form sufficiently prominent extrema in the voting matrix. If a larger amount of additional information (especially static, location-based additional information) is to be transmitted to the receiver (e.g., a mobile robot), it is advantageous to explicitly encode this additional information.

[0158] exist Figure 20 The second part of the illustration, Figure B, shows how additional, particularly static, location-based information can be explicitly transmitted to a receiver (e.g., a mobile robot): for example, it can be agreed that additional information exists at specific coordinates in a coordinate system defined by a center of symmetry, encoded, for example, in binary (black / white) or other gradients (grayscale) or color. The process then consists of two steps: in the first step, a field, such as code matrix 2010, is found based on odd and even symmetry, and the additional information is encoded in that field. In the second step, the field is read out, and thus the information contained therein. The tilted viewing angle between the imaging sensor and pattern 610 does not pose a problem here, because for the additional information to be read out, it is neither necessary for the fundamental vectors of the found coordinate system to be perpendicular to each other nor for these fundamental vectors to have the same length. Optionally, the image can also be corrected so that a Cartesian coordinate system subsequently exists. Optionally, a display can also be mounted in the field with pattern 610, which can transmit information that changes over time and / or transmits information through time changes, in addition to information that is static over time.

[0159] Through implicit error detection, high-resolution supplementary information can also be included in the pattern 610 itself. Therefore, there is another possibility that supplementary information (particularly static, position-based) is transmitted via the pattern 610 itself: this means that supplementary information is contained within the sequence of the black-and-white, color, or grayscale pattern 610 itself. Through the above classification, this supplementary information will be both implicit and explicit. Since the pattern 610, or at least some of its parts, is symmetrical, supplementary information is automatically and redundantly included, typically doubly included separately. This applies to both odd-point and even-point symmetries. This fact can be used for error correction or error detection. For example, if the pattern 610 is contaminated, for example, with bird droppings, errors resulting from this can be detected with high reliability, because the same error is unlikely to appear at the associated symmetrical location.

[0160] Figure 21 A schematic diagram illustrating the detection status using a predefined point-symmetric region 110 according to an embodiment is shown. In other words, Figure 21 A system 2100 for detecting a movable object 100 is shown. A predefined point symmetry region 110 corresponds to or is similar to one of the predefined point symmetry regions from one of the above figures. The center of symmetry 112 of the predefined point symmetry region 110 is also shown. Furthermore, an object 100 in the form of a vehicle, exemplarily shown, and a unit consisting of a camera 102 and devices 120, 140 are also shown. The object 100 can move along a direction of movement through the monitoring area between the camera 102 and the predefined point symmetry region 110.

[0161] System 2100 includes devices 120, 140 and camera 102, as well as, exemplarily, only a predefined even- and / or odd-numbered point symmetric region 110. Devices 120, 140 correspond to or are similar to those from... Figure 1 Equipment 120, 140.

[0162] In other words, Figure 21 A simple arrangement is shown, having a camera 102 and point-symmetric regions 110 located on opposite sides of a monitored area, such as a conical area or multiple monitored areas. If the object 100 obstructs the main portion of the camera's line of sight toward the point-symmetric regions 110, then during execution... Figure 3 The methods and Figure 4 The method used for detection and / or by means of Figure 1 The providing and detection equipment detected this. This arrangement, for example, allows for the counting of objects 100 moving through and between camera 102 and area 110.

[0163] Figure 22 A schematic diagram showing the detection status using a pattern 610 composed of predefined point symmetrical regions 110 according to an embodiment is shown. Figure 22The illustrations in the diagrams correspond to or are similar to Figure 21 The illustrations in the figures differ from those in that the system 2100 is provided with a pattern 610 consisting of multiple predefined point symmetric regions 110 instead of a single predefined point symmetric region. Pattern 610 corresponds to or resembles a pattern from one of the above figures. In pattern 610, the predefined point symmetric regions 110 are exemplarily arranged along a line.

[0164] In other words, in Figure 22 Multiple point-symmetric regions 110 belong to a pattern 610 observed by only one camera 102. Here, the point-symmetry center 112 is laid out on a road segment generally parallel to the direction along which the object 100 typically moves. Here, the object 100 has already obscured one point-symmetric region 110, and will successively obscure other regions 110 as the journey continues. This arrangement of regions 110 allows, for example, the determination of the speed and length of the object 100.

[0165] Figure 23 A schematic diagram illustrating the detection status using a pattern 610 composed of predefined point-symmetric regions according to an embodiment is shown. Pattern 610 corresponds to or is similar to a pattern from one of the above figures. Figure 23 The first part of the illustration, A, and the second part, B, respectively show a pattern 610 composed of multiple predefined symmetrical regions with odd-numbered points of a first center of symmetry 112A highlighted for illustration and even-numbered points of a second center of symmetry 112B highlighted for illustration. From the camera's perspective, the pattern 610 is partially obscured by an object 100, which is exemplarily implemented as a vehicle only. Furthermore, mirror images of some of the centers of symmetry 112A, 112B of the pattern 610 can be identified on a lane over which the object 100 is moving. In other words, Figure 23 The presence detection of object 100 is explained, wherein pattern 610 has a two-dimensional arrangement of point-symmetric regions.

[0166] Figure 24 A schematic diagram illustrating the detection status using a pattern 610 composed of predefined point-symmetric regions according to an embodiment is shown. Pattern 610 corresponds to or resembles a pattern from one of the above figures. More precisely, Figure 24This illustration shows a bird's-eye view of an exemplary arrangement of a system 2100 for a three-way intersection, featuring a camera 102, a pattern 610, roads 2400 for objects in the form of vehicles, pedestrians, or other traffic participants, either inside or outside a building, and two mirrors 2403, for illustrative purposes only. This arrangement, with properly aligned mirrors, allows for simultaneous monitoring of all normally used roads 2400. On each road 2400, objects normally block a beam of light twice, which is deflected between the camera 102 and the pattern 610 via the two mirrors 2403. Because the beam of light becomes narrower in the direction of the camera 102, the mirrors 2403 can be made smaller the closer they are to the camera 102 along the line of sight. Specifically, Figure 24 The diagram shows a T-junction of a passageway inside or outside a building, where people can walk on road 2400. The boundary areas indicated by dashed lines in the diagram represent walls, windows, doors, etc.

[0167] Figure 25 A schematic diagram illustrating the detection status using a pattern 610 composed of predefined point-symmetric regions according to an embodiment is shown. Pattern 610 corresponds to or resembles a pattern from one of the above figures. More precisely, Figure 25 An exemplary arrangement of a system 2100 with camera 102, pattern 610, and mirror 2403 is shown in a bird's-eye view. Here, camera 102 and pattern 610 are located on the same side of the monitored area. Camera 102 is concealed behind pattern 610 and observes through a hole in pattern 610. On the opposite side is mirror 2403, which is arranged such that camera 102 can capture a mirror image of the entire pattern 610. For this purpose, it is sufficient if mirror 2403 is only half the size of pattern 610 in both dimensions.

[0168] Especially for reference Figures 21 to 25 The following summarizes, and in other words, briefly explains, the embodiments in the context of imperceptible, passive grating substitution with hidden symmetry.

[0169] refer to Figure 3 and / or Figure 4 The described method can be used in the sense of a grating. The grating replacement implemented according to the embodiment specifically includes at least one region 110 or pattern 610 comprising one or more points of symmetry, and an imaging sensor, such as camera 102. If mirror 2403 is not used, the pattern 610 or region 110 and camera 102 are arranged on opposite sides of each other. For an example of such an arrangement, see [link to example]. Figure 21Camera 102 either has a clear view of pattern 610 or region 110, or its view is obstructed by objects 100 within it. According to embodiments, at least these two situations can be distinguished. Similar tasks, such as those performed by a classic grating, can be accomplished, for example, determining the presence of object 100 or counting objects such as people, vehicles, or objects on a conveyor belt. Compared to conventional gratings, embodiments provide some of the exemplary advantages mentioned below, which can be decisive in specific application scenarios.

[0170] This system is passive. It does not require a special light source. It can utilize existing ambient light, such as sunlight or indoor lighting. (Reference) Figure 3 and / or Figure 4 The described method works more reliably than similar image processing methods and can be performed with minimal computational effort. Fluctuations in lighting intensity, lighting color, brightness distribution, color distribution, viewing conditions, shadows, image sharpness, or arrangement do not interfere with the method because the point-symmetric properties, combined with the descriptors used, remain largely unaffected. The method can also discard a reference image of pattern 610 to compare the camera image with a reference. However, alternatively, a reference image, which can be generated temporarily, for example, when needed, can be used.

[0171] Another advantage is the imperceptibility of area 110 or pattern 610. Pattern 610 or area can be designed so that people are practically unaware of its purpose. In particular, point symmetry—especially odd-numbered point symmetry—depending on the pattern, is difficult for humans to find, even when people are looking for point symmetry. In contrast, in conventional reflective gratings, the back reflector is always visible. The advantage of imperceptibility can mean that the implementation is better protected against unauthorized manipulation, is harder for criminals to circumvent, and does not require the use of intrusive technical devices to compromise the aesthetically pleasing design of the environment (e.g., hotels, museums, residential buildings, offices, waiting rooms, landscaped gardens, etc.). However, pattern 610 with point symmetry can also be deliberately designed to be aesthetically pleasing, as symmetry is generally considered aesthetically pleasing. Most people still do not recognize the purpose of the grating.

[0172] Using this unique system allows for the monitoring of an entire road segment or surface due to the large area of ​​the camera sensor. Instead of accommodating only a single point-symmetric region 110 in pattern 610, multiple regions 110 are placed side by side, particularly for monitoring road segments; see [link to relevant documentation]. Figure 22 Or placed side-by-side and stacked vertically, especially for monitoring surfaces, see Figure 23If a road segment is monitored, the speed and length of the corresponding object 100 (e.g., a vehicle) are also determined. The speed is derived from the distance between adjacent centers of symmetry 112 or 112A, 112B and the time interval between their occlusion or exposure. The length of object 100 is derived, for example, from the number of occluded centers of symmetry 112 or 112A, 112B, or alternatively from the speed and time between the occlusion and exposure of centers of symmetry 112 or 112A, 112B. The latter approach can even be used to determine the length of object 100 that temporarily completely obscures pattern 610. If a surface is monitored, the outline of object 100 or its shadow image can also be determined at least roughly. See also Figure 23 .

[0173] Furthermore, such a system offers all the other advantages known from using camera 102 or an imaging sensor. Specifically, object 100 can be analyzed in greater detail, such as color, shape, object category, vehicle type, vehicle model, and human biometrics. No additional sensors are required besides camera 102. A vehicle, serving as an example of object 100, passes over pattern 610 in both directions of travel and temporarily obscures a portion of the point-symmetric region 110. Optionally, a mirror image of the pattern on a smooth reflective surface is also used here, in addition to pattern 610 itself, since the mirror image of the point-symmetric region 110 is itself point-symmetric. See also [reference needed]. Figure 23 The capture of symmetry centers 112 or 112A, 112B requires only a small number of computational operations, thus operating very energy-efficiently. This makes it ideal for continuous use. If object 100 has already been detected, additional algorithms can be activated as needed for more accurate analysis; these additional algorithms then allow for temporary increases in energy consumption, such as deep learning-based methods.

[0174] If the ambient light is weak, this can be compensated for by appropriately adjusting the parameters of camera 102, as described below. Opening or closing the aperture produces almost no drawbacks, especially when the camera optics are focused on pattern 610. See also... Figure 23The presence of object 100, located outside the depth of field, can still be detected. Even if pattern 610 is outside the depth of field, there is almost no degradation. Therefore, opening the aperture is a preferred option in low ambient light conditions. Extending the exposure time during image recording will not have any disadvantages, as long as the observed process is slow enough. Specifically, it is recommended that the exposure time be shorter than more than half the duration of the symmetrical region 110 of the occlusion point of object 100. Therefore, extending the exposure time is another preferred option, provided the observed process does not run too fast. However, it should be noted that increasing the gain or magnification of camera 102 does not produce a significant improvement. Adjusting the gain may be necessary to meaningfully set the value range of camera 102, but it will not lead to a significant improvement in the signal-to-noise ratio compared to the two options mentioned above.

[0175] By using one or more mirrors 2403, the monitored road segment can be extended and / or bypassed around corners without the need for additional cameras. See [link to documentation] for details. Figure 24 When pattern 610 is mirrored, its point symmetry is preserved—both its odd and even point symmetry are preserved. The corresponding mirror 2403 should be at least large enough to image pattern 610 onto camera 102 as completely as possible. This means that all mirrors 2403 are allowed to be smaller than pattern 610, and the closer a mirror 2403 is to camera 102 along the measurement path, the smaller it can be. Figure 24 This illustrates the point. Mirrors 2403, which are present anyway, can also be used or included, such as a hallway mirror. If at least one mirror 2403 is used, the camera 102 and the pattern 610 can also be placed on the same side of the area to be monitored, for example, by hiding the camera 102 behind the pattern 610, such that the camera 102 observes the mirror 2403 through a hole in the pattern, through which the camera 102 also sees the entire pattern 610. Figure 25 A corresponding embodiment is shown. The camera 102 can also be used simultaneously for a direct view of pattern 610 and for a view via one or more mirrors 2403. Figure 23 An example is shown where a mirror image on the ground meaningfully complements the direct line of sight.

[0176] If an embodiment includes an "and / or" link between a first feature and a second feature, it should be understood that the embodiment has both the first feature and the second feature according to one implementation, and either only the first feature or only the second feature according to another implementation.

Claims

1. A method (300) for providing surveillance data (135) to detect a movable object (100), wherein the method (300) comprises the following steps: Image data (105) provided by the camera (102) is read (324) from the interface (122) to the camera (102), wherein the image data (105) represents a camera image of the environment of the camera (102), wherein a pattern (610) having at least one predefined even and / or odd point symmetrical region (110; 110A, 110B) in the environment is arranged in the field of view of the camera (102), wherein, from the perspective of the camera (102), the at least one predefined even and / or odd point symmetrical region (110; 110A, 110B) can be at least partially occluded by the movable object (100); and The image data (105) and determination rules (128) are used to determine (326) the presence (112; 112A, 112B) of at least one center of symmetry of the at least one even and / or odd point symmetric region (110; 110A, 110B) in the camera image to determine the occlusion state of the movable object (100) on the at least one predefined even and / or odd point symmetric region (110; 110A, 110B), wherein the monitoring data (135) is provided according to the occlusion state, wherein the pattern (610) includes both the at least one predefined even and / or odd point symmetric region (110; 110A, 110B) and its mirror image.

2. The method (300) according to claim 1, wherein the determination rule (128) used in the determination step (326) is constructed such that A signature(s) is generated for multiple pixels of at least one segment of the camera image to obtain multiple signature(s), wherein each signature(s) is generated using a descriptor having multiple different filters, wherein each filter has at least one symmetric type, and wherein each signature(s) has a symbol for each filter of the descriptor. For the signature(s), at least one mirror signature (S) of at least one symmetric type is determined for the filter. PG S PU ), Check whether the pixel having the signature(s) exists in at least one other pixel in the search area (1104) of the environment surrounding the pixel, the at least one other pixel having a corresponding mirror signature(s). PG S PU The signature(s) is used to determine the pixel coordinates of at least one symmetric signature pair from the pixel and the other pixel when at least one other pixel is present. And evaluate the pixel coordinates of the at least one symmetric signature pair to identify the at least one center of symmetry (112; 112A, 112B). And / or at least one reflector (R) PG R PU The symbol applied to one of the signatures(s) is used to determine the at least one mirror signature(S). PG S PU ), where each reflector (R) PG R PU ) has rules for modifying the symbol that are specific to the symmetry type and depend on the descriptor, wherein the search region (1104) depends on the applied reflector (R PG R PU At least one reflector in ).

3. The method (300) according to claim 2, wherein in the determining step (326), for each determined center of symmetry (112; 112A, 112B), using the pixel coordinates of each symmetry signature pair that has contributed to correctly identifying the center of symmetry (112; 112A, 112B), a transformation rule is determined for transforming the pixel coordinates of the center of symmetry (112; 112A, 112B) and / or the at least one even and / or odd point symmetry region (110; 110A, 110B), wherein the transformation rule is applied to the pixel coordinates of the center of symmetry (112; 112A, 112B) and / or the at least one even and / or odd point symmetry region (110; 110A, 110B) to correct the distorted viewpoint of the camera image.

4. The method (300) according to any one of claims 1 to 3, comprising the step (330): comparing at least one center of symmetry (112; 112A, 112B) from the camera image with at least one reference center of symmetry from the reference data (115) in terms of intensity, intensity variation over time and / or local intensity variation, to determine an intensity-related deviation (131) between the center of symmetry (112; 112A, 112B) and the reference center of symmetry, wherein the monitoring data (135) is provided based on the deviation (131).

5. The method (300) according to any one of claims 1 to 3, wherein in the determining step (326), the symmetry type of the at least one symmetry center (112; 112A, 112B) is determined, wherein the symmetry type represents even-point symmetry and / or odd-point symmetry, and / or in the comparing step (330), the symmetry type of the at least one symmetry center (112; 112A, 112B) in the camera image is compared with a predefined symmetry type of at least one reference symmetry center from reference data (115) to check the consistency between the at least one symmetry center (112; 112A, 112B) and the at least one reference symmetry center.

6. The method (300) according to claim 5, wherein the image data (105) read in the reading step (324) represents a camera image of at least one pattern (610; 1710, 1810) consisting of a plurality of predefined even and / or odd point symmetric regions (110; 110A, 110B), wherein the geometric arrangement of the symmetry centers (112; 112A, 112B) of the at least one pattern (610; 1710, 1810) is determined in the determining step (326), the geometric sequence of the symmetry type of the symmetry centers (112; 112A, 112B) is determined, and / or the pattern (610; 1710, 1810) is determined from a plurality of predefined patterns using the sequence, wherein the arrangement and / or the sequence represents an identifier of the pattern (610; 1710, 1810).

7. The method (300) of claim 6, wherein in the determining step (326), the arrangement of the centers of symmetry (112; 112A, 112B) of the at least one pattern (610; 1710, 1810) and / or the sequence of the symmetry types of the centers of symmetry (112; 112A, 112B) are used to determine implicit additional information of the at least one pattern (610; 1710, 1810) or readout rules for reading explicit additional information in the camera image, wherein the arrangement and / or the sequence represent the additional information in an encoded form, wherein the additional information relates to the detection of the movable object (100).

8. The method (300) according to any one of claims 6 to 7, wherein the determination step (326) and / or comparison step (330) are performed jointly for all centers of symmetry (112; 112A, 112B) independently of the symmetry type of the centers of symmetry (112; 112A, 112B), or the determination step (326) and / or comparison step (330) are performed individually for centers of symmetry (112; 112A, 112B) of the same symmetry type according to the symmetry type of the centers of symmetry (112; 112A, 112B).

9. A method (400) for detecting a movable object (100), wherein the method (400) comprises the following steps: The evaluation (444) assesses the monitoring data (135) provided by the method (300) according to any one of claims 1 to 8 to generate a detection signal (145) dependent on the monitoring data (135); and The detection signal (145) is output to the interface (148) of the processing unit used to perform the grating function in order to perform the detection of the movable object (100).

10. A method (500) for manufacturing at least one predefined even- and / or odd-point symmetric region (110; 110A, 110B) for use in the method (300; 400) according to any one of claims 1 to 9, wherein the method (500) comprises the following steps: Generate (502) design data (204), the design data representing a graphical representation of the at least one predefined even and / or odd point symmetric region (110; 110A, 110B); and Using the design data (204), at the display medium (600) or in the display medium (600), generate (506) the at least one predefined even and / or odd point symmetric region (110; 110A, 110B) to manufacture the at least one predefined even and / or odd point symmetric region (110; 110A, 110B).

11. The method (500) according to claim 10, wherein design data (204) is generated in the generation step (502), the design data being a graphical representation of the at least one predefined even and / or odd point symmetrical region (110; 110A, 110B) as a circle, ellipse, polygon, or annulus, wherein the at least one predefined even and / or odd point symmetrical region (110; 110A, 110B) has a regular or quasi-random content pattern, and / or wherein any of the at least one predefined even and / or odd points are predefined. The first half of the symmetrical region (110; 110A, 110B) is constructed, and the second half is constructed by point mirroring and / or inversion of grayscale values ​​and / or color values, and / or wherein the at least one predefined even and / or odd point symmetrical region (110; 110A, 110B) is generated in the generation step (506) by additive manufacturing process, separation, coating, forming, primary forming or optical display, and / or wherein the display medium (600) has glass, stone, ceramic, plastic, rubber, metal, concrete, plaster, paper, food or optical display device.

12. The method (500) according to any one of claims 10 to 11, wherein design data (204) is generated in the generation step (502), the design data representing a graphical representation of at least one pattern (610; 1710, 1810) consisting of a plurality of predefined even and / or odd point symmetric regions (100; 110A, 110B), wherein at least one subset of the point symmetric regions (100; 110A, 110B) is aligned on a regular or irregular grid (1311), directly adjacent to each other and / or separated from at least one adjacent even and / or odd point symmetric region (110; 110A, 110B) by gap portions, and is the same or different from each other in terms of their size and / or their content patterns and / or arranged in a common plane or in different planes, wherein the design data (204) representing a graphical representation of at least one pattern (610; 1710, 1810) having layered symmetry is generated in the generation step (502).

13. An apparatus configured to perform and / or manipulate the steps of the method according to any one of claims 1 to 12 in a corresponding unit.

14. A system (2100) for detecting a movable object (100), wherein the system (2100) has the following characteristics: The device according to claim 13; At least one camera (102), wherein the camera (102) and the device are capable of or have been connected to each other in a manner that enables data transmission; and At least one predefined even and / or odd point symmetrical region (110; 110A, 110B) is manufactured by the method (500) according to any one of claims 10 to 12, wherein the region (110; 110A, 110B) can or has been arranged in the field of view of the camera (102).

15. A computer program product configured to perform and / or manipulate the steps of the method according to any one of claims 1 to 12.

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