Optical motion mode sensing system and method

Abstract

The invention relates to an optical motion mode sensing system and method, the system comprises an image sensor, an image processing module and a motion inspection module, and the method comprises the steps of collecting a dynamic image, processing the image, generating and sensing a specific event cloud and converting the state of a state machine. According to the optical motion mode sensing system and method disclosed by the invention, the light intensity change caused by the motion of the object is sensed through the image sensor, the sensing of the moving target is realized, and compared with the traditional recognition technology, the system and the method can meet the requirement of man-machine interaction on higher motion precision towards artificial intelligence development; meanwhile, compared with a novel identification mode, the optical motion mode sensing system and method disclosed by the invention do not need to extract basic information and process a background, so that the data volume is reduced; binary or low-precision digital signals can be generated according to light intensity change perception, the computing power is greatly reduced, the implementation threshold is lowered, and the method is suitable for many application programs of the Internet of Things.

Description

Technical Field

[0001] The present invention belongs to the field of motion perception technology, and in particular relates to an optical motion pattern perception system and method. Background Art

[0002] Human-computer interaction technology has been a hot topic in the development of artificial intelligence in recent years, and motion sensing or recognition technology is an important foundation for human-computer interaction. Currently, common motion sensing or recognition technologies on the market can be divided into two categories: one is the traditional recognition method based on infrared thermal sensing and wireless radio frequency recognition, and the other is a new recognition method represented by face recognition that requires feature value extraction and deep learning algorithms.

[0003] Among them, infrared thermal sensing relies on the infrared rays emitted by the object itself to sense whether there are obstacles in the preset area, and wireless radio frequency identification technology requires the configuration of radio frequency cards to transmit radio frequency signals in a specific area to achieve sensing, and can only work within the range of transmitting radio frequency signals. Whether it is infrared sensing or wireless radio frequency identification, this traditional recognition method can only achieve sensing or recognition when the target is stationary or moving at a low speed. It cannot detect the movement of the target in space and cannot perceive the moving target. Since traditional recognition technology cannot form images and cannot make accurate judgments based on images, the application scenarios are limited, and thus it cannot be applied to the development of human-computer interaction towards artificial intelligence, which requires higher motion accuracy. The new recognition method uses a combination of hardware and software. By collecting images and further processing the images, the spatial motion correlation is established, which can improve the reliability of recognition and is gradually becoming popular. Taking face recognition as an example, first of all, face recognition requires the pre-collection of basic information such as face information, and the extraction of feature values ​​from the key points of the face, and then the use of deep learning software (such as the widely used neural network learning algorithm) to further process the face image. Emerging identification methods rely heavily on the collected basic data, and also require a set of increasingly complex algorithms to train the basic data to form a huge data set, which further increases the complexity of the algorithm. In pursuit of reliability, this type of identification method not only has an increasing amount of data, but also increasingly complex algorithms and higher computing power, which undoubtedly raises the threshold for implementation and the difficulty of implementation is increasing. For many IoT applications, they require solutions with less data and easier implementation, and these new identification methods are not so universal.

[0004] It can be seen from this that traditional recognition technologies such as infrared thermal sensing and wireless radio frequency identification cannot be used to meet the needs of human-computer interaction towards artificial intelligence, which requires higher motion accuracy, because they cannot perceive moving targets. New recognition methods represented by face recognition focus on software and neglect hardware, resulting in increasing data volumes, increasingly complex algorithms, higher computing power, and increasing difficulty in implementation, which in turn limits their application. Summary of the invention

[0005] In view of the above problems, the purpose of the present invention is to provide an optical motion pattern perception system and method, which is used to solve the problem that traditional recognition technologies such as infrared thermal sensing and wireless radio frequency identification cannot perceive moving targets and cannot be applied to the development of human-computer interaction towards artificial intelligence, which requires higher motion accuracy. New recognition methods represented by face recognition focus on software and neglect hardware, resulting in increasing amounts of data, increasingly complex algorithms, higher computing power, and increasing difficulty in implementation, which in turn limits their application.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention discloses an optical motion pattern sensing system, comprising:

[0008] At least one image sensor collects images in real time, and changes in light intensity trigger pixel events in its pixels. The output formed by all pixel events of the image sensor constitutes an event cloud;

[0009] At least one image processing module predefines a path on the image and predefines a number of specific areas on the path, and sets a trigger pixel threshold for each specific area. When the number of pixels changed in a specific area exceeds its trigger pixel threshold, the specific area is triggered to form a specific event cloud;

[0010] At least one motion detection module, comprising at least one state machine, the state machine having N states, wherein N is a positive integer greater than 1, the state machine selecting a state from a set of N states as an initial state, the state machine being controlled by a digital signal generated by the image sensor according to a specific event cloud, and generating a plurality of control signals according to the state of the state machine;

[0011] Among them, the image sensor collects images in real time and generates a dynamic event cloud; the event cloud moves on the image along the path predefined by the image processing module, and passes through these specific areas in sequence according to the time series. If the number of pixels changed in a specific area exceeds the trigger pixel threshold, the specific area is triggered to form a specific event cloud; the image sensor senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal, and transmits the digital signal to the motion detection module; until the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific area of ​​the path, the motion detection module generates multiple control signals according to the state of the state machine that needs to change, so as to realize the state transition of the state machine.

[0012] Furthermore, it also includes a timing monitor, which can record the time of a specific event cloud in real time and is associated with the state machine of the motion inspection module, and can return the state machine to an initial state;

[0013] Once the state of the state machine encounters a deadlock phenomenon or a timeout phenomenon, the timing monitor returns the state machine to an initial state according to the control signal or timeout information generated by the motion inspection module.

[0014] Specifically, the image sensor is a motion image sensor, which includes a pixel matrix and a pixel control circuit, each pixel has a pixel structure including a photodetector and a storage unit, the pixel control circuit is capable of sequentially writing photodetection values ​​representing after exposure to the storage unit of the pixel, and the image sensor also includes a comparison circuit, which is used to store sequential photodetection values ​​of at least part of the pixels, to compare the sequential photodetection values, to generate a comparison signal based on the sequential photodetection values ​​of the pixels, and to generate a comparison matrix reflecting image changes from the comparison signal.

[0015] Specifically, the image processing module and the motion detection module are integrated on the image sensor.

[0016] Furthermore, a controller is included, and the image sensor, the image processing module, the motion detection module and the timing monitor are independent of each other and are respectively connected to the controller.

[0017] Furthermore, it includes multiple image sensors, which are arranged in a manner to expand the field of view of perceived motion as much as possible; the multiple image sensors are connected to the controller in sequence or separately; each image sensor is configured with an image processing module, and each image sensor predefines paths on the image captured by the corresponding image sensor to form multiple paths, and predefines several specific areas on each path, and the several specific areas of the multiple paths are associated with one or more state machines.

[0018] Furthermore, it includes multiple image processing modules, which are respectively connected to the image sensor or respectively connected to the controller; the multiple image processing modules predefine paths on an image captured by an image sensor to form multiple paths, and predefine several specific areas on each path, and the several specific areas of the multiple paths are associated with one or more state machines.

[0019] In a second aspect, the present invention discloses an optical motion pattern sensing method, comprising:

[0020] Dynamic image acquisition: The image sensor acquires images in real time, and changes in light intensity trigger pixel events in its pixels. The output formed by all pixel events of the image sensor constitutes an event cloud;

[0021] Image processing: the image processing module predefines a path on the image and predefines a number of specific areas on the path;

[0022] Generation and perception of specific event clouds: the event cloud moves along the path on the image and passes through these specific areas in sequence according to the time series. If the number of pixels changed in a specific area exceeds its trigger pixel threshold, the specific area is triggered to form a specific event cloud; the image sensor senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal, and transmits the digital signal to the motion detection module;

[0023] State transition of the state machine: until the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event clouds in the specific areas of the path, the motion inspection module generates multiple control signals according to the states that need to change in the state machine to realize the state transition of the state machine.

[0024] Furthermore, while the image sensor senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal and transmits the digital signal to the motion detection module, the image sensor also transmits the digital signal to a timing monitor, and the occurrence time of the specific event cloud is recorded in real time by the timing monitor;

[0025] And once the state of the state machine encounters a deadlock phenomenon or a timeout phenomenon, the timing monitor returns the state machine to an initial state according to the control signal or timeout information generated by the motion inspection module.

[0026] Specifically, the predefined path is: a straight line or an arc in which the hand of the subject waves from the left to the right or from the right to the left;

[0027] The predefined several specific areas are: a first specific area and a second specific area are predefined on the left and right sides of the path respectively;

[0028] The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, thereby realizing the state conversion of the state machine: the event cloud passes through the first specific area and the second specific area along the path. If the first specific area and the second specific area are triggered in sequence in chronological order to form the first specific event cloud and the second specific event cloud respectively, then starting from the initial state, the first specific event cloud is generated first and then the second specific event cloud is generated, and the state machine generates one state; conversely, starting from the initial state, the second specific event cloud is generated first and then the first specific event cloud is generated, and the state machine generates another state.

[0029] Specifically, the predefined path is: the route that the perceived person's feet walk from outside the door to inside the door in sequence;

[0030] The predefined several specific areas are: according to the foot walking from the outside to the inside in chronological order, a third specific area, a fourth specific area and a fifth specific area are predefined in sequence from the outside to the inside on the path;

[0031] The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, thereby realizing the state conversion of the state machine: the event cloud passes through the third specific area, the fourth specific area and the fifth specific area along the path. If the third specific area, the fourth specific area and the fifth specific area are triggered in sequence according to the chronological order, forming the third specific event cloud, the fourth specific event cloud and the fifth specific event cloud respectively, then starting from the initial state, the third specific event cloud is generated first, then the fourth specific event cloud is generated, and finally the fifth specific event cloud is generated, and the state of the state machine is converted.

[0032] Specifically, the predefined path is: the route that the perceived person walks through from outside the window through the window into the window;

[0033] The predefined several specific areas are: according to the perceived person passing through the window from outside the window to inside the window, and then moving away from the window in chronological order, a sixth specific area, a seventh specific area and an eighth specific area are predefined in sequence on the path;

[0034] The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and realizes the state conversion of the state machine: the event cloud passes through the sixth specific area, the seventh specific area and the eighth specific area along the path. If the sixth specific area, the seventh specific area and the eighth specific area are triggered in chronological order, forming the sixth specific event cloud, the seventh specific event cloud and the eighth specific event cloud respectively, then starting from the initial state, the sixth specific event cloud is generated first, then the seventh specific event cloud is generated, and finally the eighth specific event cloud is generated, and the state of the state machine is converted.

[0035] In a third aspect, the present invention further discloses the application of the above optical motion pattern sensing method to hand-wave switches, automatic doors or window intrusion alarms.

[0036] The present invention adopts the above technical solution, which has the following advantages:

[0037] (I) The present invention proposes an optical motion pattern perception system and method, wherein an image sensor collects images in real time, and changes in light intensity trigger pixel events in its pixels, and the output formed by all pixel events is defined as an event cloud; an image processing module predefines a path on the image, and predefines several specific areas on the path; the event cloud moves along the path on the image, and passes through these specific areas in sequence according to a time sequence, and if the number of pixels changed in a specific area exceeds its triggering pixel threshold, the specific area is triggered to form a specific event cloud; the image sensor senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal, and transmits the digital signal to the motion detection module and the timing monitor, and the occurrence time of the specific event cloud is recorded in real time by the timing monitor; until the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific area of ​​the path, the motion detection module generates multiple control signals according to the state that the state machine needs to change, and realizes the state transition of the state machine. Wherein, once the state machine encounters a deadlock phenomenon or a timeout phenomenon, the timing monitor returns the state machine to the initial state according to the control signal or timeout information generated by the motion detection module. The optical motion pattern perception system and method disclosed in the present invention senses the light intensity change caused by the motion of the object through an image sensor, thereby realizing the perception of the moving target. Compared with traditional recognition technologies such as infrared thermal sensing and wireless radio frequency recognition, it can meet the needs of human-computer interaction towards artificial intelligence, which requires higher motion accuracy. At the same time, compared with new recognition methods represented by face recognition that are software-heavy and hardware-light, the optical motion pattern perception system and method disclosed in the present invention, firstly, does not need to extract basic information and process background, thus reducing the amount of data; secondly, it can generate binary or low-precision digital signals based on the perception of light intensity changes, greatly reducing computing power, thereby lowering the threshold for implementation, and ultimately enabling a large number of wide applications.

[0038] (II) The development trend of emphasizing software and neglecting hardware in the emerging recognition technology combining hardware and software, and the "wrong" cognition gradually generated by this development trend in the field of artificial intelligence, that is, the larger the data, the more complex the algorithm, and the more accurate the recognition result. Therefore, in order to obtain accurate recognition results, it is necessary to further increase the research on deep learning algorithms. However, this development idea increases the difficulty of realizing emerging recognition technologies, thereby limiting their promotion and application. The present invention discloses an optical motion pattern perception system and method. According to the fact that the movement of an object will cause changes in light intensity, the image sensor senses the changes in light intensity caused by the movement of the object, and automatically removes the background without motion, thereby realizing the perception of the moving target, without the need to extract basic information and process the background, and reducing the amount of data; it can generate binary or low-precision digital signals based on the perception of light intensity changes, greatly reducing the demand for computing power and further reducing the complexity. Therefore, compared with the emerging recognition method, the present invention provides a technical solution with a technical concept that is completely different from the existing sensing and recognition technology, and its motion recognition accuracy is high, and the technical effect reaches or even exceeds the existing emerging recognition technology, overcoming the problems that have arisen in recent years due to the development of emphasizing software and neglecting hardware. The technical bias formed by the "wrong" cognition that has gradually emerged in the field of artificial intelligence is due to the trend. That is, it is possible to obtain highly accurate motion recognition without extracting significant information and reducing the required computing power. Furthermore, with the increasing demand for smaller and easier-to-implement motion recognition and human-computer interaction solutions in IoT applications, the present invention may cause researchers and engineers in the fields of motion perception, human-computer interaction and even artificial intelligence to rethink the development trend of heavy software and light hardware in the emerging recognition technology that combines hardware and software, causing relevant researchers to pay attention to hardware, and guide more people to invest more in research on the induction of motion image sensors based on changes in light intensity caused by the movement of objects.

[0039] (III) The present invention discloses an optical motion pattern perception system and method, wherein the optical motion pattern perception system can be used as a motion-based human-computer interaction device and can be implemented by a simple motion image sensor and a simple hardware or software time state machine; since moving objects usually only occupy a small part of the scene, such as waving hands, foot movements, etc., such movements can be sensed by motion-sensitive image sensors to obtain a sparse and binary image, which greatly reduces the amount of data and increases the useful information content of the data. This makes the optical motion pattern perception system and method disclosed in the present invention require less data and are easier to implement, further lowering the threshold for implementation. The optical motion pattern perception system and method disclosed in the present invention have a wide range of application scenarios, such as gesture control, motion control, gait sensing, number of people, contactless door opening, etc. For many IOT (Internet of Things) applications that require smaller data volumes and cheaper solutions, the present invention can be universally implemented. Whether compared with traditional recognition technologies and emerging recognition technologies, or in terms of the technical effects of recognition and sensing, or even in terms of promotion and application, many aspects have confirmed that the present invention provides a fast, efficient and economical solution based on motion perception. Moreover, from the current perspective, whether in terms of perception devices or perception methods, the optical motion pattern perception system and method disclosed in the present invention can be considered to be highly optimized in human-computer interaction configurations.

[0040] (IV) The present invention discloses an optical motion pattern perception system and method, wherein the image sensor used in the system has a new sensor architecture, including a pixel matrix and a pixel control circuit, wherein each time an image is captured, a pixel matrix of the same size as the image is generated, and the pixel control circuit encodes the image changes in a simple data format according to the local temporal light intensity changes of each pixel of two consecutive images, and generates pixel-by-pixel outputs. For example, the pixel values ​​of pixels at the same position of two consecutive images are compared, and if there is no change, a NULL value is output, and if there is a change, a positive output is activated when the pixel value increases (increases in brightness), or a negative output is activated when the pixel value decreases (decreases in brightness). In order to display it more intuitively, it can be assumed that the color representing the output NULL value is white, the color representing the positive output is red, and the color representing the negative output is blue. Then the optical motion pattern perception system and method disclosed in the present invention, the image sensor of which displays to the user the image: the part where the light intensity changes presents a dynamic alternation of red and blue, the part where the light intensity does not change becomes the background, and can be statically presented in colors such as white, so the area that needs to display the changes is reduced, further reducing the amount of data; at the same time, since static photos are not directly generated and only dynamic images of the local light intensity changes are displayed, the target person cannot be effectively identified. Therefore, the present invention provides privacy protection for people who are regarded as motion perception objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a working principle diagram of an optical motion pattern perception system disclosed in Embodiment 1 of the present invention, including an image sensor and an image processing module;

[0042] Figure 2 is a working principle diagram of an optical motion pattern perception system disclosed in Embodiment 1 of the present invention, including an image sensor and two image processing modules;

[0043] Figure 3 is an application example diagram of a waving switch in the optical motion pattern sensing method disclosed in Embodiment 2 of the present invention, wherein Figure 3 (I) is a schematic diagram of predefined paths and specific areas on the image. Figure 3 (Ⅱ) is the corresponding state machine diagram;

[0044] Figure 4 is an application example diagram of an automatic door in the optical motion pattern sensing method disclosed in Example 2 of the present invention, wherein Figure 4 (I) is a schematic diagram of predefined paths and specific areas on the image. Figure 4 (Ⅱ) is the corresponding state machine diagram;

[0045] Figure 5 is an application example diagram of the window intrusion alarm in the optical motion pattern sensing method disclosed in Example 2 of the present invention, wherein Figure 5 (I) is a schematic diagram of predefined paths and specific areas on the image. Figure 5 (Ⅱ) is the corresponding state machine diagram.

[0046] Description of reference numerals:

[0047] a-image sensor, b-image processing module, c-motion detection module, d-timing monitor;

[0048] 100-image, 101-path, 102-specific area;

[0049] A1-first specific area, B1-second specific area, A2-third specific area, B2-fourth specific area, C2-fifth specific area, C3-sixth specific area, B3-seventh specific area, A3-eighth specific area;

[0050] ZA1-first specific event cloud, ZB1-second specific event cloud, ZA2-third specific event cloud, ZB2-fourth specific event cloud, ZC2-fifth specific event cloud, ZC3-sixth specific event cloud, ZB3-seventh specific event cloud, ZA3-eighth specific event cloud. DETAILED DESCRIPTION

[0051] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0052] At present, emerging recognition methods such as face recognition, which combine hardware and software, not only have more and more data in order to pursue reliability, but also increasingly complex algorithms, and higher and higher computing power requirements, which are more difficult to implement, and show a development trend of emphasizing software and neglecting hardware. The development of this emerging recognition method excessively pursues the complexity of the algorithm, and gradually produces a wrong perception in the field of artificial intelligence, that is, the larger the data, the more complex the algorithm, the more accurate the recognition result, and even forms a technical bias against simplifying significant information and reducing computing power to still obtain accurate results. The emergence of this technical bias has substantially restricted the development of motion sensing technology.

[0053] Studies have shown that the movement of objects usually causes changes in light intensity, which can be sensed by optical sensors. Therefore, it is feasible to perceive moving targets through optical-based sensors.

[0054] Due to the "event" perception of light, the background can be considered to be "erased" (some noise may appear on the background due to noise in the sensor), and each moving object will produce a "trigger" pixel cloud in the event image. In a well-designed human-computer interaction system, the complexity of the motion pattern can be simplified to achieve simplicity and increase reliability. However, this "event" (local light intensity changes are considered to be triggered by some event) image must be further processed.

[0055] In order to simplify the extraction of significant information and reduce the required computing power, some smart sensing pixel arrays have been proposed, such as "Improved CMOS Image Sensor". The Chinese invention patent "Improved CMOS Image Sensor" with application number 202210132353.1 proposes some smart sensing pixel arrays, which can provide an image in which each pixel value is sensitive to local temporal light intensity changes, and generates binary or low-precision digital signals according to the light intensity changes. These digital signals are usually binary. Using these smart sensing pixel arrays, dynamically changing images can be generated. Such a device is an optical-based sensor that can sense whether the target is moving in space, so it is also called a motion sensing sensor.

[0056] The present invention is based on the above principle, and can realize the perception of moving targets according to the changes in light intensity caused by the movement of the object through a motion sensing sensor.

[0057] It is worth mentioning that the dynamic image captured by the motion sensing sensor used in the present invention is not a grayscale or color video image. This is because the dynamic image obtained by the motion sensing sensor used in the present invention only presents binary or low-precision numerical changes (dynamic event clouds) in the area where the light intensity changes, and no information is output in the area where the light intensity does not change (so there is no need to process the background), and it can be considered that the background has not changed. However, in the video recording, not only the area where the light intensity changes is recorded and output, but also the area where the light intensity does not change is recorded and output; the image processing system of the video needs to process the image to distinguish useful moving objects. On the contrary, the motion sensing sensor of the present invention does not need to process the background, which not only reduces the processing complexity, but also ensures the privacy in the image.

[0058] The optical motion pattern perception system disclosed in the present invention includes an image sensor, an image processing module, a motion detection module and a timing monitor. The image sensor collects images in real time and generates an event based on the sensitivity of each pixel to the local time light intensity change. The events generated by all pixels of the image sensor together constitute a dynamic event cloud, and a binary or low-precision digital signal is generated based on the perception of a specific event cloud according to the light intensity change; the image processing module predefines a path on the image and predefines a number of specific areas on the path, and a trigger pixel threshold is set for each specific area. When the number of pixels changed in the specific area exceeds its trigger pixel threshold, the specific area is triggered to form a specific event cloud; the motion detection module includes at least one state machine, the state machine has N states, wherein N is a positive integer greater than 1, and the state machine selects a state as an initial state from the set of N states, and the state machine is controlled by the digital signal generated by the image sensor according to the specific event cloud, and generates multiple control signals according to the state of the state machine; the timing monitor can record the time of the specific event cloud in real time, and is associated with the state machine of the motion detection module, and can return the state machine to the initial state. Compared with traditional recognition technologies such as infrared thermal sensing and wireless radio frequency identification, the system and method disclosed in the present invention can meet the needs of human-computer interaction developing towards artificial intelligence, which requires higher motion accuracy. Compared with new recognition methods that focus on software and light on hardware, such as face recognition, the optical motion pattern perception method disclosed in the present invention not only does not need to extract basic information, but also does not need to process the background, thus reducing the amount of data. It can generate binary or low-precision digital signals based on the perception of light intensity changes, greatly reducing the demand for computing power, thereby lowering the threshold for implementation and ultimately enabling massive applications.

[0059] Embodiment 1: An optical motion pattern sensing system

[0060] Embodiment 1 provides an optical motion pattern sensing system, and its structure is described in detail below with reference to the accompanying drawings.

[0061] refer to Figure 1 The optical motion pattern perception system mainly includes four main parts, namely, an image sensor a, an image processing module b and a motion detection module c, and may also include a timing monitor d, and the motion detection module c and the timing monitor d are connected.

[0062] Image sensor a captures image 100, and changes in light intensity trigger pixel events in its pixels. The output formed by all pixel events of the image sensor a constitutes an event cloud.

[0063] The image processing module b has the function of processing the generated image 100, that is, predefining a path 101 on the image 100 and predefining a number of specific areas 102 on the path 101. A trigger pixel threshold is set for each specific area 102. When the number of pixels changed in a specific area 102 exceeds its trigger pixel threshold, the specific area 102 is triggered to form a specific event cloud.

[0064] A motion detection module c includes at least one state machine, the state machine has N states, wherein N is a positive integer greater than 1, the state machine selects one state from a set of N states as an initial state, the state machine is controlled by a digital signal generated by an image sensor a according to a specific event cloud, and generates a plurality of control signals according to the state of the state machine;

[0065] The timing monitor d can record the time of a specific event cloud in real time and is associated with the state machine, so as to return the state machine to an initial state.

[0066] Among them, the image sensor a collects images 100 in real time and generates a dynamic event cloud;

[0067] When the event cloud moves along the path 101 predefined by the image processing module b on the image 100 and passes through the specific areas 102 in sequence according to the time sequence, if the number of pixels changed in a specific area 102 exceeds the trigger pixel threshold, the specific area 102 is triggered to form a specific event cloud; the image sensor a senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal, and transmits the digital signal to the motion detection module c;

[0068] Once the state of the state machine encounters a deadlock or timeout phenomenon, the timing monitor d returns the state machine to the initial state according to the control signal generated by the motion inspection module c or the timeout information built into it;

[0069] Until the timing relationship between the specific event clouds triggered by these specific areas 102 meets the specific requirements of the event cloud in the specific area 102 of the path 101, the motion inspection module c generates multiple control signals according to the state of the state machine that needs to change, thereby realizing the state transition of the state machine.

[0070] Although the event cloud crosses these predefined specific areas in a predefined time sequence, the exact absolute time order of these crossings is not stable, but the relative logical time sequence is stable. The intersection of a predefined specific area on the image 100 can be determined by a simple trigger pixel threshold.

[0071] The motion detection module c is capable of detecting motion patterns of a state machine, each motion pattern detection is performed by a predetermined token-based state machine. The state machine has N states, and the state-to-state transition of the token is enabled by a specific event cloud crossing over a predefined specific area. When the token reaches a specific state, it is considered that a motion pattern is detected.

[0072] Among them, when the state machine encounters a deadlock phenomenon, an abnormal situation will occur. This abnormal situation can occur during the movement of the event cloud along the path 101, and can also occur when the event cloud ends moving along the path 101. Specifically, the abnormal situation is caused by different reasons, including unexpected movement patterns, noise or light pollution, etc.

[0073] The state of the state machine encounters a timeout phenomenon, which includes not only the time gap timeout between specific event clouds during the movement of the event cloud along path 101, but also the time when the event cloud ends moving along path 101 and the non-initial state state expires, and the state machine needs to return to the initial state.

[0074] It can be seen that no matter an abnormal situation occurs during the movement of the event cloud along the path 101, or the event cloud ends its movement along the path 101, as long as the state of the state machine encounters a deadlock phenomenon or a timeout phenomenon, the timing monitor d returns the state machine to the initial state. For example, when the time gap between specific event clouds times out, the timing monitor d resets the state machine and returns the state machine to the initial state. Another example is that different reasons such as unexpected movement patterns, noise or light pollution may cause deadlock problems, which can be eliminated by resetting the state machine through the timing monitor d.

[0075] Specifically, the image sensor a is a motion image sensor, which includes a pixel matrix and a pixel control circuit, each pixel has a pixel structure including a photodetector and a storage unit, the pixel control circuit is capable of sequentially writing photodetection values ​​representing after exposure to the storage unit of the pixel, and the image sensor a further includes a comparison circuit, which is used to store sequential photodetection values ​​of at least part of the pixels, to compare the sequential photodetection values, to generate a comparison signal based on the sequential photodetection values ​​of the pixels, and to generate a comparison matrix reflecting changes in the image 100 from the comparison signal.

[0076] It should be noted that, firstly, the motion image sensor is an image sensor with special functions, which has the basic function of acquiring images as an image sensor; secondly, the motion image sensor has a pixel matrix and a pixel control circuit, each pixel of which is sensitive to changes in local temporal light intensity and generates an event. All pixels on the pixel matrix of the motion image sensor together constitute a dynamic event cloud based on all events generated by their sensitivity to changes in local temporal light intensity.

[0077] The event cloud is a collection of many events. If an event generated by a pixel is called a "raindrop", then the collection of events generated by many pixels together constitutes a "cloud", and the area sensitive to light intensity changes in this "cloud" will change dynamically, so the image 100 obtained by the motion image sensor is a dynamic image.

[0078] When the event cloud moves on the image 100 along the path 101 predefined by the image processing module b, passing through a specific area 102 predefined on the path 101, if the number of pixels changed in a specific area 102 exceeds the trigger pixel threshold, the specific area 102 is triggered to form a specific event cloud.

[0079] Finally, since it has a comparison circuit that stores sequential photoelectric detection values ​​and compares sequential photoelectric detection values, it can generate a comparison signal based on the sequential photoelectric detection values ​​of the pixels, and generate a comparison matrix that reflects the changes in the image 100 from the comparison signal. Therefore, the motion image sensor can perceive specific events based on changes in light intensity and generate binary or low-precision digital signals, and transmit the digital signals to the motion detection module c. This enables the motion image sensor to have the ability to detect and compare calculations, and can detect changes in motion patterns.

[0080] Regarding motion image sensors, Shanghai Honggan Microelectronics Technology Co., Ltd. has applied for a patent. For more specific structures, please refer to the Chinese invention patent "Improved CMOS Image Sensor" with application number 202210132353.1, which will not be repeated here.

[0081] Specifically, the timing monitor d is a watchdog timer, whose English name is Watchdog timer.

[0082] Specifically, the image processing module b and the motion detection module c can be in either hardware or software form.

[0083] The image processing module b and the motion detection module c are respectively connected to the image sensor a.

[0084] As a specific implementation, the image processing module b and the motion detection module c are integrated on the image sensor a to form an image sensor a that is motion-sensitive and intelligent, and a timing monitor d associated with a motion / time-based state machine, together forming the two major hardware blocks of the optical motion pattern perception system.

[0085] As another specific implementation, the image sensor a, the image processing module b, the motion detection module c and the timing monitor d can be independent of each other. When these four components are independent of each other, preferably, the optical motion pattern perception system also includes a controller, which can be specifically used to determine whether the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific area 102 of the path 101. The image sensor a, the image processing module b, the motion detection module c and the timing monitor d are respectively connected to the controller. In this case, the image sensor a is more like a camera, which can sensitively generate dynamic images according to the changes in the local time light intensity. The calculation functions of the calculation processing and the judgment processing are handed over to the controller.

[0086] Regarding the optical motion pattern perception system disclosed in the present invention, its application method can be further extended. For example, in order to obtain a larger field of view, a common implementation is that the optical motion pattern perception system includes a plurality of image sensors a, and the plurality of image sensors a are arranged in a manner to expand the field of view of the perceived motion as much as possible;

[0087] The plurality of image sensors a are connected to the controller in sequence or respectively;

[0088] Each image sensor a is configured with an image processing module b. Each image sensor a predefines a path 101 on the image 100 captured by the corresponding image sensor a to form multiple paths 101, and predefines a number of specific areas 102 on each path 101. The several specific areas 102 of the multiple paths 101 are associated with one or more state machines.

[0089] In order to obtain a larger field of view, another specific implementation is to adjust the field of view angle of the image sensor a so that the image sensor a has a large field of view. The optical motion pattern sensing system includes a plurality of image processing modules b, and the plurality of image processing modules b are respectively connected to one image sensor a or respectively connected to a controller;

[0090] The plurality of image processing modules b predefine paths 101 on an image 100 captured by an image sensor a to form a plurality of paths 101, and predefine a plurality of specific areas 102 on each path 101, such as Figure 2 As shown;

[0091] Certain areas 102 of the plurality of paths 101 are associated with one or more state machines.

[0092] The above specific implementations of obtaining a larger field of view can all realize multiple paths 101 for detecting intrusion, and are applicable to the scenario of application example 3. Regardless of the method, it is within the protection scope of the optical motion pattern perception system disclosed in the present invention.

[0093] Embodiment 2: A method for sensing optical motion patterns

[0094] Embodiment 2 provides an optical motion pattern sensing method, using the optical motion pattern sensing system of embodiment 1, the method comprising the following steps:

[0095] Dynamic image acquisition: Image sensor a acquires image 100 in real time, and changes in light intensity trigger pixel events in its pixels. The output formed by all pixel events of the image sensor a constitutes an event cloud;

[0096] Image processing: the image processing module b predefines a path 101 on the image 100 and predefines a number of specific areas 102 on the path 101;

[0097] Generation and perception of a specific event cloud: the event cloud moves along a path 101 on the image 100 and passes through the specific regions 102 in sequence according to a time series. If the number of pixels changed in a specific region 102 exceeds its trigger pixel threshold, the specific region 102 is triggered to form a specific event cloud;

[0098] The image sensor a senses the specific event cloud according to the change of light intensity and generates a binary or low-precision digital signal, and transmits the digital signal to the motion detection module c and the timing monitor d. The occurrence time of the specific event cloud is recorded in real time by the timing monitor d;

[0099] State transition of the state machine: until the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event clouds in the specific areas of the path, the motion inspection module c generates multiple control signals according to the state that needs to be changed in the state machine to realize the state transition of the state machine;

[0100] Wherein, once the state machine encounters a deadlock or timeout phenomenon, the timing monitor d returns the state machine to the initial state according to the control signal or timeout information generated by the motion inspection module c.

[0101] Specifically, when the state machine encounters a deadlock phenomenon, an abnormal situation will occur. This abnormal situation may occur during the movement of the event cloud along the path 101, or may occur at the end of the movement of the event cloud along the path 101. Specifically, the abnormal situation is caused by different reasons, including unexpected movement patterns, noise or light pollution, etc.

[0102] The state of the state machine encounters a timeout phenomenon, which includes not only the time gap timeout between specific event clouds during the movement of the event cloud along the path 101, but also the time timeout when the event cloud ends moving along the path 101. Regardless of the time timeout, the state machine needs to return to the initial state.

[0103] Among them, "the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event clouds in the specific areas of the path, and the state transition of the state machine is realized" needs to be determined according to the specific application scenario. The following provides three specific application examples of the optical motion pattern perception method applied to the waving switch, automatic door or window intrusion alarm, respectively, to further illustrate how the present invention uses the optical motion pattern perception method disclosed in the present invention to realize the state transition of the state machine.

[0104] Application Example 1: Wave Switch

[0105] Inductive switches are often encountered in life. The wave switch is a common inductive switch. The following takes a simple wave switch as an example.

[0106] refer to Figure 3 First, according to the needs of the perceived person, for example, the hand waving from the left to the right is defined as "open", and the hand waving from the right to the left is defined as "closed", and the path 101 can be predefined as the perceived hand waving from the left to the right or from the right to the left, and two specific areas 102 can be predefined on the predefined path 101: a first specific area A1 and a second specific area B1, such as Figure 3 As shown in (Ⅰ).

[0107] Correspondingly, the state machine diagram can be defined as follows: if the first specific area A1 and the second specific area B1 are triggered in chronological order, forming the first specific event cloud ZA1 and the second specific event cloud ZB1 respectively, then starting from the initial state, the first specific event cloud ZA1 is generated first, and then the second specific event cloud ZB1 is generated, then the state machine generates a state - "open"; conversely, starting from the initial state, the second specific event cloud ZB1 is generated first, and then the first specific event cloud ZA1 is generated, then the state machine generates another state - "closed", such as Figure 3 (Ⅱ) as shown.

[0108] Based on the above analysis of application example 1, it can be summarized as follows:

[0109] The predefined path is: a straight line or an arc when the hand of the subject waves from the left to the right or from the right to the left;

[0110] The predefined several specific areas are: a first specific area A1 and a second specific area B1 are predefined on the left and right sides of the path 101 respectively;

[0111] The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and realizes the state conversion of the state machine: the event cloud passes through the first specific area A1 and the second specific area B1 along the path 101. If the first specific area A1 and the second specific area B1 are triggered in sequence according to the chronological order, forming the first specific event cloud ZA1 and the second specific event cloud ZB1 respectively, then starting from the initial state, the first specific event cloud ZA1 is generated first, and then the second specific event cloud ZB1 is generated, then the state machine generates one state; conversely, starting from the initial state, the second specific event cloud ZB1 is generated first, and then the first specific event cloud ZA1 is generated, then the state machine generates another state.

[0112] Application Example 2: Automatic Door

[0113] As a non-contact door opening method, the automatic door is very useful for the physical contact between people and the environment. A very simple automatic door can be designed using the present invention.

[0114] refer to Figure 4 First, according to the sensed person being outside the door, the sensed person's feet walk from outside to inside in chronological order, and three specific areas 102 can be predefined in front of the door: the third specific area A2, the fourth specific area B2 and the fifth specific area C2, such as Figure 4 As shown in (Ⅰ).

[0115] Accordingly, the state machine diagram can be defined as: starting from the initial state, the third specific event cloud ZA2 is generated first, then the fourth specific event cloud ZB2 is generated, and finally the fifth specific event cloud ZC2 is generated, then the state of the state machine is converted - "open the door", such as Figure 4 (Ⅱ) as shown.

[0116] Based on the above analysis of application example 2, it can be summarized as follows:

[0117] The predefined path is: the route that the perceived person's feet walk from outside the door to inside the door in sequence;

[0118] The predefined several specific areas are: according to the foot walking from the outside to the inside in chronological order, a third specific area A2, a fourth specific area B2 and a fifth specific area C2 are predefined from the outside to the inside on the path 101;

[0119] The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and the state conversion of the state machine is realized as follows: the event cloud passes through the third specific area A2, the fourth specific area B2 and the fifth specific area C2 along the path 101. If the third specific area A2, the fourth specific area B2 and the fifth specific area C2 are triggered in chronological order, forming the third specific event cloud ZA2, the fourth specific event cloud ZB2 and the fifth specific event cloud ZC2 respectively, then starting from the initial state, the third specific event cloud ZA2 is generated first, then the fourth specific event cloud ZB2 is generated, and finally the fifth specific event cloud ZC2 is generated, and the state of the state machine is converted.

[0120] Application Example 3: Window Break-in Alarm

[0121] Somewhat similar to the previous application example, the intrusion motion is characterized by extending from the outside to the inside via a specific path 101, such as through a window, through an unlocked door. Therefore, the motion pattern from the outside to the inside can be detected and a high presumption of intrusion can be defined.

[0122] refer to Figure 5 First, after the perceived person climbs over the window, the perceived person passes by the window in chronological order from near to far, and three specific areas 102 can be defined in the window: the sixth specific area C3, the seventh specific area B3 and the eighth specific area A3, as shown in FIG. Figure 5 As shown in (Ⅰ).

[0123] Accordingly, the state machine diagram can be defined as: starting from the initial state, the sixth specific event cloud ZC3 is generated first, then the seventh specific event cloud ZB3 is generated, and finally the eighth specific event cloud ZA3 is generated, then the state of the state machine changes to "alarm", such as Figure 5(Ⅱ) shown.

[0124] Based on the above analysis of application example 3, it can be summarized as follows:

[0125] The predefined path is: the route that the perceived person walks through from outside the window to inside the window;

[0126] The predefined several specific areas are: according to the perceived person passing through the window from outside the window into the window, and moving away from the window in chronological order, a sixth specific area C3, a seventh specific area B3 and an eighth specific area A3 are predefined in sequence on the path 101;

[0127] The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and realizes the state conversion of the state machine: the event cloud passes through the sixth specific area C3, the seventh specific area B3 and the eighth specific area A3 along the path 101. If the sixth specific area C3, the seventh specific area B3 and the eighth specific area A3 are triggered in chronological order, forming the sixth specific event cloud ZC3, the seventh specific event cloud ZB3 and the eighth specific event cloud ZA3 respectively, then starting from the initial state, the sixth specific event cloud ZC3 is generated first, then the seventh specific event cloud ZB3 is generated, and finally the eighth specific event cloud ZA3 is generated, and the state of the state machine is converted.

[0128] However, in practice, since a building has more than one window, in order to monitor multiple windows of a building, it is necessary to monitor multiple windows simultaneously, which requires a larger field of view to monitor multiple intrusion paths 101 .

[0129] Furthermore, how to obtain a larger field of view? One way is to increase the number of image sensors a, and multiple image sensors a are arranged in a manner to expand the field of view of perceived motion as much as possible; another way is to increase the number of pixel matrices inside the image sensor a so that a single image sensor a obtains a large field of view, and then increase the number of image processing modules b, which requires a larger monitoring field of view and simultaneous monitoring of multiple paths 101.

[0130] Among them, whether entering from the door or breaking in from the window, application examples 2 and 3 are similar. The "temporal relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event clouds in the specific areas of the path, and realizes the state transition of the state machine" of these two application examples can be summarized as follows:

[0131] The event cloud passes through three specific areas along the path 101. If the three specific areas are triggered in chronological order and form three specific event clouds respectively, then starting from the initial state, three specific event clouds are generated in sequence, and the state of the state machine is transformed, such as Figure 4 and Figure 5 shown.

[0132] It can be seen from this that the optical motion pattern perception method provided in Example 2 has a wide range of applications.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An optical motion pattern sensing system, characterized in that: include At least one image sensor (a) collects images (100) in real time, and triggers pixel events in its pixels due to changes in light intensity, and the output formed by all pixel events of the image sensor (a) constitutes an event cloud; At least one image processing module (b) predefines a path (101) on the image (100), and predefines a plurality of specific areas (102) on the path (101), wherein a trigger pixel threshold is set for each specific area (102), and when the number of pixels changed in a specific area (102) exceeds its trigger pixel threshold, the specific area (102) is triggered to form a specific event cloud; at least one motion detection module (c), comprising at least one state machine, the state machine having N states, wherein N is a positive integer greater than 1, the state machine selecting a state from a set of N states as an initial state, the state machine being controlled by a digital signal generated by the image sensor (a) according to a specific event cloud, and generating a plurality of control signals according to the state of the state machine; The image sensor (a) collects images (100) in real time to generate a dynamic event cloud; the event cloud moves on the image (100) along a path (101) predefined by the image processing module (b), and passes through the specific areas (102) in sequence according to a time sequence. If the number of pixels changed in a specific area (102) exceeds the trigger pixel threshold, the specific area (102) is triggered to form a specific event cloud; the image sensor (a) senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal, and transmits the digital signal to the motion detection module (c); until the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific area (102) of the path (101), the motion detection module (c) generates a plurality of control signals according to the state of the state machine that needs to change, so as to realize the state transition of the state machine.

2. The optical motion pattern sensing system according to claim 1, characterized in that: It also includes a timing monitor (d), which can record the time of a specific event cloud in real time and is associated with the state machine of the motion inspection module (c) to return the state machine to an initial state; Once the state of the state machine encounters a deadlock phenomenon or a timeout phenomenon, the timing monitor (d) returns the state machine to an initial state according to the control signal or timeout information generated by the motion inspection module (c).

3. The optical motion pattern sensing system according to claim 1 or 2, characterized in that: The image sensor (a) is a motion image sensor, which includes a pixel matrix and a pixel control circuit, each pixel has a pixel structure including a photodetector and a storage unit, the pixel control circuit is capable of sequentially writing photodetection values ​​representing after exposure to the storage unit of the pixel, and the image sensor (a) also includes a comparison circuit, which is used to store the sequential photodetection values ​​of at least part of the pixels, to compare the sequential photodetection values, to generate a comparison signal based on the sequential photodetection values ​​of the pixels, and to generate a comparison matrix reflecting image changes from the comparison signal.

4. The optical motion pattern sensing system according to claim 3, characterized in that: The image processing module (b) and the motion detection module (c) are integrated on the image sensor (a).

5. The optical motion pattern sensing system according to any one of claims 1 to 3, characterized in that: The system further comprises a controller, wherein the image sensor (a), the image processing module (b), the motion detection module (c) and the timing monitor (d) are independent of each other and are respectively connected to the controller.

6. The optical motion pattern sensing system according to claim 3 or 5, characterized in that: The device comprises a plurality of image sensors (a), wherein the plurality of image sensors (a) are arranged in a manner to maximize the field of view for sensing motion; The plurality of image sensors (a) are connected to the controller in sequence or respectively; Each image sensor (a) is equipped with an image processing module (b), each image sensor (a) predefines a path (101) on an image (100) captured by the corresponding image sensor (a) to form a plurality of paths (101), and predefines a plurality of specific areas (102) on each path (101), Certain areas (102) of the plurality of paths (101) are associated with one or more state machines.

7. The optical motion pattern sensing system according to claim 3 or 5, characterized in that: comprising a plurality of image processing modules (b), wherein the plurality of image processing modules (b) are respectively connected to the image sensor (a) or respectively connected to the controller; A plurality of image processing modules (b) predefine paths (101) on an image (100) captured by an image sensor (a) to form a plurality of paths (101), and predefine a plurality of specific areas (102) on each path (101). Certain areas (102) of the plurality of paths (101) are associated with one or more state machines.

8. An optical motion pattern sensing method, characterized in that: include Dynamic image acquisition: The image sensor (a) acquires images (100) in real time, and changes in light intensity trigger pixel events in its pixels. The output formed by all pixel events of the image sensor (a) constitutes an event cloud; Image processing: the image processing module (b) predefines a path (101) on the image (100), and predefines a number of specific areas (102) on the path (101); Generation and perception of a specific event cloud: the event cloud moves along a path (101) on an image (100) and passes through the specific areas in sequence according to a time sequence. If the number of pixels changed in a specific area (102) exceeds its trigger pixel threshold, the specific area (102) is triggered to form a specific event cloud; the image sensor (a) senses the specific event cloud according to the change in light intensity to generate a binary or low-precision digital signal, and transmits the digital signal to a motion detection module (c); State transition of the state machine: until the timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific area (102) of the path (101), the motion inspection module (c) generates multiple control signals according to the state of the state machine that needs to change, thereby realizing the state transition of the state machine.

9. The optical motion pattern sensing method according to claim 8, characterized in that: When the image sensor (a) senses the specific event cloud according to the change of light intensity, generates a binary or low-precision digital signal, and transmits the digital signal to the motion detection module (c), the image sensor (a) also transmits the digital signal to the timing monitor (d), and the occurrence time of the specific event cloud is recorded in real time by the timing monitor (d); And once the state of the state machine encounters a deadlock phenomenon or a timeout phenomenon, the timing monitor (d) returns the state machine to an initial state according to the control signal or timeout information generated by the motion inspection module (c).

10. The optical motion pattern sensing method according to claim 9, characterized in that: The predefined path is: a straight line or an arc when the hand of the subject waves from the left to the right or from the right to the left; The predefined specific areas are: a first specific area (A1) and a second specific area (B1) are respectively predefined on the left and right sides of the path (101); The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and the state conversion of the state machine is realized as follows: the event cloud passes through the first specific area (A1) and the second specific area (B1) along the path (101). If the first specific area (A1) and the second specific area (B1) are triggered in sequence according to the chronological order to form the first specific event cloud (ZA1) and the second specific event cloud (ZB1), respectively, then starting from the initial state, the first specific event cloud (ZA1) is generated first, and then the second specific event cloud (ZB1) is generated, and the state machine generates one state; conversely, starting from the initial state, the second specific event cloud (ZB1) is generated first, and then the first specific event cloud (ZA1) is generated, and then the state machine generates another state.

11. The optical motion pattern sensing method according to claim 9, characterized in that: The predefined path is: the route that the perceived person's feet walk from outside the door to inside the door in sequence; The predefined several specific areas are: according to the foot walking from the outside to the inside in chronological order, a third specific area (A2), a fourth specific area (B2) and a fifth specific area (C2) are predefined from the outside to the inside on the path (101); The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and the state conversion of the state machine is realized as follows: the event cloud passes through the third specific area (A2), the fourth specific area (B2) and the fifth specific area (C2) along the path (101). If the third specific area (A2), the fourth specific area (B2) and the fifth specific area (C2) are triggered in chronological order, forming the third specific event cloud (ZA2), the fourth specific event cloud (ZB2) and the fifth specific event cloud (ZC2) respectively, then starting from the initial state, the third specific event cloud (ZA2) is generated first, then the fourth specific event cloud (ZB2) is generated, and finally the fifth specific event cloud (ZC2) is generated, and the state of the state machine is converted.

12. The optical motion pattern sensing method according to claim 9, characterized in that: The predefined path is: the route that the perceived person walks through from outside the window to inside the window; The predefined specific areas are: a sixth specific area (C3), a seventh specific area (B3) and an eighth specific area (A3) are predefined in sequence on the path (101) after the perceived person passes through the window from outside the window and enters the window, and then moves away from the window in chronological order; The timing relationship between the specific event clouds triggered by these specific areas meets the specific requirements of the event cloud in the specific areas of the path, and the state conversion of the state machine is realized as follows: the event cloud passes through the sixth specific area (C3), the seventh specific area (B3) and the eighth specific area (A3) along the path (101). If the sixth specific area (C3), the seventh specific area (B3) and the eighth specific area (A3) are triggered in chronological order, forming the sixth specific event cloud (ZC3), the seventh specific event cloud (ZB3) and the eighth specific event cloud (ZA3) respectively, then starting from the initial state, the sixth specific event cloud (ZC3) is generated first, then the seventh specific event cloud (ZB3) is generated, and finally the eighth specific event cloud (ZA3) is generated, and the state of the state machine is converted.

13. Application of the optical motion pattern sensing method according to claim 8 or 9 in hand-wave switches, automatic doors or window intrusion alarms.

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