Object detection methods and apparatus, imaging devices and storage media

Abstract

This application relates to an object detection method and apparatus, a camera device, and a storage medium. The method includes: acquiring a tabletop image; determining a detection contour line of the tabletop and a contour line of an object on the tabletop in the tabletop image; and determining that the object on the tabletop has a tendency to fall if the detection contour line of the tabletop is tangent to and / or intersects with the contour line of the object. By determining the positional relationship between the object and the edge of the tabletop through the relationship between the contour lines, it is possible to quickly and accurately determine whether an object has a tendency to fall.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to object detection methods and apparatus, camera devices and storage media. Background Technology

[0002] If objects placed on a tabletop fall, they may cause breakage, property damage, or even personal injury. Therefore, being able to detect in time whether objects on the tabletop are about to fall is a crucial step in preventing them from falling. A related technology, "A Coffee Table for Preventing Objects from Falling" (publication number CN110338566A), proposes a coffee table designed to prevent items from falling to the ground. The key design element is to add a locking mechanism and several additional tabletop panels to the original coffee table components—tabletop, support frame, and legs. The added locking mechanism exposes these additional tabletop panels, thereby preventing items from falling.

[0003] The technical solutions in the related technologies require modification of the physical structure, which is costly and not suitable for modification on all types of tables. Therefore, there is an urgent need for an accurate and low-cost object detection method for objects on tables. Summary of the Invention

[0004] This application provides an object detection method, apparatus, electronic device, and storage medium to at least address the problem of high cost in preventing objects from falling in related technologies.

[0005] In a first aspect, embodiments of this application provide an object detection method, including:

[0006] Obtain the tabletop image;

[0007] Determine the detection contour line of the tabletop and the contour line of the object on the tabletop in the tabletop image;

[0008] If the detection contour line of the platform is determined to be tangent to and / or intersect with the contour line of the object, it is determined that there is a tendency for the object to fall onto the platform.

[0009] The object detection methods provided in the various embodiments of this application can determine whether there is a tendency for an object to fall from a tabletop based on a tabletop image. This method can determine the falling trend without modifying the tabletop or other physical structures. Specifically, after acquiring the tabletop image, the detection contour lines of the tabletop and the contour lines of the objects on the tabletop can be extracted from the image. If the detection contour lines of the tabletop and the contour lines of the objects are determined to be tangent and / or intersecting, it is determined that there is a tendency for an object to fall from the tabletop. By determining the positional relationship between the object and the edge of the tabletop through the relationship between the contour lines, it is possible to quickly and accurately determine whether an object has a falling trend.

[0010] Optionally, in one embodiment of this application, determining the detection contour line of the tabletop in the tabletop image includes:

[0011] Determine the outline of the tabletop in the tabletop image;

[0012] The contour line on the other side, which is lower than the platform, is used as the detection contour line of the platform.

[0013] Optionally, in one embodiment of this application, determining that there is a tendency for an object to fall from the table surface when the detection contour line of the table surface is tangent to and / or intersects with the contour line of the object includes:

[0014] If it is determined that the detection contour line of the platform is tangent to and / or intersects with the contour line of the object, the duration of the tangency and / or intersection is determined.

[0015] If the duration is greater than or equal to a preset duration threshold, it is determined that there is a tendency for objects to fall onto the platform.

[0016] Optionally, in one embodiment of this application, after determining the detection contour line of the tabletop and the contour line of the object on the tabletop in the tabletop image, the method further includes:

[0017] Determine the vertical angle between the camera device used to capture the image of the tabletop and the target object;

[0018] If the vertical angle is determined to be greater than the preset angle, the height of the target object, the contact point on the contact surface between the target object and the table that is closest to the detection contour line, and the distance between the contact point and the detection contour line are obtained.

[0019] Based on the height and the distance, determine whether the vertical projection of the object on the table exceeds the detection contour line;

[0020] If the vertical projection is determined to exceed the detection contour line, it is determined that the object has a tendency to fall.

[0021] Optionally, in one embodiment of this application, acquiring the tabletop image includes:

[0022] Acquire an image of the environment to be detected;

[0023] Image recognition is performed on the image of the environment to be detected to obtain the tabletop image.

[0024] Optionally, in one embodiment of this application, after determining that there is a tendency for an object to fall onto the table, the method further includes:

[0025] Issue an alarm message.

[0026] Secondly, embodiments of this application also provide an object detection device, comprising:

[0027] The image acquisition module is used to acquire images of the tabletop.

[0028] The contour line determination module is used to determine the detected contour line of the tabletop and the contour line of the object on the tabletop in the tabletop image;

[0029] The falling trend determination module is used to determine that there is a falling trend of an object on the table when the detection contour line of the table surface is tangent to and / or intersects with the contour line of the object.

[0030] Thirdly, a camera device includes a lens assembly, an image sensor, a memory, and a processor, characterized in that the memory stores a computer program, and the processor is configured to run the computer program to perform the object detection method.

[0031] Fourthly, a non-volatile computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the object detection method.

[0032] Fifthly, a computer program product includes computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device executes the object detection method.

[0033] In a sixth aspect, a chip includes at least one processor for running a computer program or computer instructions stored in a memory to perform the object detection method described above.

[0034] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0035] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0036] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0037] Figure 2 This is a flowchart of the object detection method provided in the embodiments of this application;

[0038] Figure 3 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0039] Figure 4 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0040] Figure 5 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0041] Figure 6 This is a schematic diagram of the module structure of the object detection device provided in the embodiments of this application;

[0042] Figure 7 This is a schematic diagram of the module structure of the processing device provided in the embodiments of this application;

[0043] Figure 8 This is a schematic diagram of the module structure of the computer program product provided in the embodiments of this application. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application. Furthermore, it is understood that although the efforts made in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, modifications to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0045] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0046] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application means two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The terms “first,” “second,” “third,” etc., used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0047] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed description. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, apparatus, means, elements, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0048] To clearly illustrate the technical solutions of the various embodiments of this application, the following describes... Figure 1 The application environment of the embodiments of this application will be described.

[0049] See Figure 1 , Figure 1 This is a schematic diagram of an application scenario provided in an embodiment of this application. Figure 1This application demonstrates the application of the object detection method provided in this embodiment to a kitchen scenario. Specifically, a camera device 101 can be used to detect objects on the kitchen countertop 103, where kitchen utensils, tableware, kitchen appliances, and other objects 105 can be placed. This application embodiment provides an object detection device, which can include various forms such as electronic devices, non-volatile computer-readable storage media, computer program products, and chips. As an electronic device, the object detection device can transmit data with the camera device 101 and process the countertop image captured by the camera device 101. As a non-volatile computer-readable storage medium, computer program product, or chip, the object detection device can be coupled to the interior of the camera device 101, enabling the camera device 101 to have object detection functionality. Alternatively, the object detection device can be placed in other terminals (such as smartphones), servers, or the cloud, and the tabletop image captured by the camera device 101 can be sent to the other terminals, servers, or the cloud via network transmission or other means. After the other terminals, servers, or the cloud complete the object detection, they can send the detection results back to the camera device 101 or the user terminal.

[0050] The camera device 101 may include any electronic device with image capture capabilities. Optionally, in one embodiment of this application, the camera device 101 may include a depth camera, wherein the depth camera may further include cameras based on technologies such as time-of-flight (TOF), structured light, and binocular depth vision, etc., which are not limited herein.

[0051] It should be noted that the object detection methods and objects detection devices provided in the various embodiments of this application can not only detect objects on and on kitchen countertops, but also be applied to object detection in various scenarios such as coffee tables, dressing tables, and chemical laboratory workbenches. The embodiments of this application do not impose any limitations.

[0052] The object detection method described in this application will be explained in detail below with reference to the accompanying drawings. Figure 2 This is a flowchart illustrating one embodiment of the object detection method provided in this application. Although this application provides method operation steps as shown in the following embodiments or figures, the method may include more or fewer operation steps based on conventional or non-inventive methods. For steps that do not logically have a necessary causal relationship, the execution order of these steps is not limited to the execution order provided in the embodiments of this application. In actual object detection processes or when the method is executed, it can be executed in the order shown in the embodiments or figures, or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0053] Specifically, one embodiment of the object detection method provided in this application is as follows: Figure 2 As shown, the method may include:

[0054] S201: Obtain the tabletop image.

[0055] In this embodiment, the tabletop image can refer to an image including the tabletop and objects on it. Of course, when using the camera device 101 to capture the tabletop image, at least one parameter such as the position, angle, and focal length of the camera device 101 can be pre-adjusted so that the captured image matches the size of the tabletop to be detected. However, in some cases, the captured image may not match the size of the tabletop to be detected; in this case, the captured image may include not only the tabletop image but also images of other objects such as the ground and windows. Therefore, in one embodiment of this application, an image of the environment to be detected can be obtained, and then the tabletop image can be identified from the image of the environment to be detected using image recognition or other methods. Specifically, for example, machine learning can be used to identify the tabletop image from the image of the environment to be detected; this application does not impose any limitations on this method.

[0056] S203: Determine the detection contour line of the tabletop and the contour line of the object on the tabletop in the tabletop image.

[0057] In this embodiment, the detection contour line may include the contour line of the platform for which object detection is required. In one embodiment, the detection contour line may include the entire contour line of the platform. In one embodiment, the detection contour line may include the outermost contour line of the platform. In one embodiment, the detection contour line can be determined based on the height difference between the two sides of the contour line. Specifically, determining the detection contour line of the platform in the platform image may include:

[0058] S301: Determine the outline of the tabletop in the tabletop image;

[0059] S303: Use the outline of the other side, which is lower than the platform, as the detection outline of the platform.

[0060] In this embodiment, firstly, the outline of the tabletop can be determined based on the tabletop image. However, some parts of the outline may be the intersection lines between the tabletop and the wall, or between the tabletop and the user's body, and the length or position of such intersection lines may not be fixed. Since step S205 of this embodiment determines that there is a tendency for an object to fall from the tabletop when the outline of the tabletop and the outline of the object are tangent, in the above situation, if the object is placed against the wall, based on the above method, since the outline of the object is tangent to the detection outline of the tabletop, incorrect detection results may be obtained. Therefore, in this embodiment, the height of the object on the other side of the outline can be compared with the height of the tabletop. If the height on the other side is higher than the tabletop, it can be determined that there is no risk of the object falling from the tabletop; otherwise, there is a risk of the object falling from the tabletop. In this embodiment, during the comparison of the height of the outline and the tabletop, a depth image can be used to determine whether the other side of the outline is higher than the tabletop. For example, the platform image can be acquired using a depth camera. Then, the height difference between the two sides of the contour line can be determined based on the platform image, and the detection contour line of the platform can be determined based on the height difference.

[0061] It should be noted that before determining the outline of the objects on the table, object detection can be performed on the table image to detect the objects on the table. For example, a bounding box can be used to circle the corresponding objects, and even the object's category can be labeled. Based on this, contour detection can be performed on the image of the object circled by the bounding box, which can improve the targeting and accuracy of contour detection. Furthermore, based on the object's category, it can be determined whether the object is fragile or dangerous. For other non-fragile, non-dangerous, or live animals, such as plastic bags, paper boxes, rubber gloves, and pet cats, detection is unnecessary to avoid giving users unnecessary warnings.

[0062] In one embodiment of this application, an edge detection algorithm can be used to determine the contour lines of the platform and the objects on the platform. The edge detection operators may include the Roberts Cross operator, Prewitt operator, Sobel operator, Kirsch operator, Marr-Hildreth operator, Canny operator, Laplacian operator, etc. Of course, in addition to the edge detection algorithm, other contour detection algorithms such as contour tracking algorithms, image subset-based algorithms, and run-length-based algorithms may also be used, and this application does not impose any limitations on these algorithms.

[0063] S205: If it is determined that the detection contour line of the platform is tangent to and / or intersects with the contour line of the object, it is determined that there is a tendency for the object to fall on the platform.

[0064] In real-world scenarios, if the outline of an object projected onto a table comes into contact with, or is tangent to, and / or intersects with, the detection outline of the table, it can be determined that there is a tendency for an object to fall onto the table. Figure 3 The image shows the detection outline of the countertop and the outlines of the bowl and knife on the countertop, such as... Figure 3 As shown, the outlines of the bowl and the knife both intersect with the detected outline of the countertop. Specifically, in determining whether they are tangent or intersecting, firstly, the mathematical expressions for the detected outline of the countertop and the outline of the object can be determined. This is especially important for objects with regular shapes, such as circles, ellipses, straight lines, squares, and spiral curves, where mathematical expressions can accurately represent the shape characteristics. By determining whether there is an intersection point between the data expressions of the detected outline and the outline of the object, it can be determined whether the detected outline of the countertop is tangent to and / or intersects with the outline of the object. For outlines that are difficult to express using data expressions, algorithms such as Hough circle detection can be used to determine whether the detected outline of the countertop is tangent to and / or intersects with the outline of the object. Of course, any algorithm can be used to determine whether the detected outline intersects with and / or intersects with the outline of the object; this application does not impose any limitations on this.

[0065] In real-world scenarios, when a user picks up an object from a table, the object's outline may come into contact with the table's detection outline, but this contact is usually very brief. Therefore, in one embodiment of this application, determining that an object is likely to fall from the table when the detection outline of the table is tangent to or intersects with the object's outline includes:

[0066] S401: When the detection contour line of the platform is tangent to and / or intersects with the contour line of the object, determine the duration of the tangency and / or intersection.

[0067] S403: If the duration is greater than or equal to a preset duration threshold, it is determined that there is a tendency for an object to fall onto the table.

[0068] In this embodiment, if the duration for which the object's outline is tangent to and / or intersects with the detection outline of the platform is greater than or equal to a preset duration threshold, it can be determined that there is a tendency for an object to fall onto the platform. This preset duration threshold can be set to, for example, 1 second, 2 seconds, etc., and is not limited thereto in this application.

[0069] In this embodiment, by setting the time as described above, we can prevent misjudgments caused by the brief movement of the object due to the user picking it up, thereby further improving the detection accuracy.

[0070] The camera is mounted directly above the tabletop. In this way, the outline of the object in the captured image is the outline of its vertical projection onto the tabletop. Ideally, the presence of a potential object falling from the tabletop is determined by whether the detected outline of the tabletop and the outline of the object's vertical projection intersect and / or are tangent. However, in practical applications, the camera cannot always be mounted directly above the tabletop. In this case, the outline of the object in the captured image is the outline of its projection at the angle between the object and the camera. Figure 4 As shown, the camera device is deviated from the tabletop at too large an angle. Although the salad bowl appears to be about to fall from the image, based on whether the outlines intersect and / or are tangent, it might be concluded that there is no tendency for the object to fall from the tabletop. Therefore, to more accurately determine whether an object has a tendency to fall, in one embodiment of this application, after determining the detection outline of the tabletop and the outline of the object on the tabletop in the tabletop image, the method further includes:

[0071] S501: Determine the vertical angle between the camera device used to capture the image of the tabletop and the target object;

[0072] S503: When it is determined that the vertical angle is greater than the preset angle, the height of the target object, the contact point on the contact surface between the target object and the table that is closest to the detection contour line, and the distance between the contact point and the detection contour line are obtained.

[0073] S505: Based on the height and the distance, determine whether the vertical projection of the object on the table exceeds the detection contour line;

[0074] S507: If it is determined that the vertical projection exceeds the detection contour line, it is determined that the object has a tendency to fall.

[0075] The following is in conjunction with the appendix Figure 5 The implementation methods of the above embodiments are described below. Figure 5 yes Figure 4 A magnified view of the area within the elliptical dashed line region. First, the vertical angle between the camera device and the target object can be determined. This vertical angle refers to the angle between the line connecting the camera device and the target object and the vertical line. Optionally, the vertical angle may include the vertical angle between the camera device and a target point on the target object. The target point may include the contact point on the contact surface between the target object and the platform that is closest to the detection contour line. Figure 5 Point B in the middle, such as Figure 4 As shown, ∠A is the vertical angle in this case. In other embodiments, the vertical angle may also include the vertical angle between the camera device and any point on the target object. If the vertical angle is determined to be greater than a preset angle, the height of the target object, the contact point on the contact surface between the target object and the table that is closest to the detection contour line, and the distance between the contact point and the detection contour line are obtained. For example, the preset angle can be set to 45 degrees, 60 degrees, etc., without limitation. The height of the target object is obtained as H1, and the distance between the contact point B and the detection contour line is obtained as L1. The value of angle α can be calculated based on feature points A and B, and the value of L2 can be calculated as H1 / tanα based on H1 and α. When L2 > L1, it can be determined that the contour line of the vertical projection of the target object intersects with the detection contour line of the table, and the target object is at risk of falling.

[0076] It should be noted that the execution order of embodiments S401-S403 and embodiments S501-S507 is not important; they can be executed in parallel or sequentially, and no restriction is placed here.

[0077] In one embodiment of this application, if it is determined that there is a tendency for an object to fall onto the table, an alarm message can be issued. Specifically, the alarm message can be issued in various ways. In one embodiment, a preset sound signal, including but not limited to warning sounds and voice prompts, can be played through a speaker coupled to the inside or outside of the camera device. In other embodiments, the alarm message can be sent through a user client. If the camera device has corresponding client software, the alarm message can be pushed to the client software. This application does not limit the method of issuing the alarm message.

[0078] The object detection methods provided in the various embodiments of this application can determine whether there is a tendency for an object to fall from a tabletop based on a tabletop image. This method can determine the falling trend without modifying the tabletop or other physical structures. Specifically, after acquiring the tabletop image, the detection contour lines of the tabletop and the contour lines of the objects on the tabletop can be extracted from the image. If the detection contour lines of the tabletop and the contour lines of the objects are determined to be tangent and / or intersecting, it is determined that there is a tendency for an object to fall from the tabletop. By determining the positional relationship between the object and the edge of the tabletop through the relationship between the contour lines, it is possible to quickly and accurately determine whether an object has a falling trend.

[0079] Embodiments of this application also provide an object detection device, such as... Figure 6 As shown, the object detection module 600 may include:

[0080] Image acquisition module 601 is used to acquire tabletop images;

[0081] The contour line determination module 603 is used to determine the detected contour line of the table surface and the contour line of the object on the table surface in the table surface image;

[0082] The falling trend determination module 605 is used to determine that there is a falling trend of an object on the table when the detection contour line of the table surface is tangent to and / or intersects with the contour line of the object.

[0083] Embodiments of this application also provide a camera device, including a lens assembly, an image sensor, a memory, and a processor. The memory stores a computer program, and the processor is configured to run the computer program to execute the methods described in any of the above embodiments. The lens assembly may include multiple lenses (convex or concave lenses) for acquiring light signals reflected from a tabletop and objects on the tabletop, and transmitting the acquired light signals to the image sensor. The image sensor generates a raw image of the tabletop and objects based on the light signals.

[0084] Embodiments of this application also provide a processing device 700, which can be a physical device or a cluster of physical devices, or a virtualized cloud device, such as at least one cloud computing device in a cloud computing cluster. For ease of understanding, this application illustrates the structure of the processing device 700 as an independent physical device.

[0085] like Figure 7 As shown, the processing device 700 includes a processor and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-described means when executing the instructions. The processing device 700 includes a memory 701, a processor 703, a bus 705, and a communication interface 707. The memory 701, processor 703, and communication interface 707 communicate via the bus 701. The bus 705 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 7 The symbol is represented by only one thick line, but this does not indicate that there is only one bus or one type of bus. Communication interface 707 is used for communication with external devices.

[0086] The processor 703 may be a central processing unit (CPU). The memory 701 may include volatile memory, such as random access memory (RAM). The memory 701 may also include non-volatile memory, such as read-only memory (ROM), flash memory, HDD, or SSD.

[0087] The memory 701 stores executable code, and the processor 703 executes the executable code to perform the aforementioned test scenario construction method.

[0088] Embodiments of this application provide a non-volatile computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the above-described method.

[0089] Embodiments of this application provide a computer program product including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.

[0090] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), electrically programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital video disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing.

[0091] The computer-readable program instructions or code described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0092] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as "C" or similar languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from computer-readable program instructions. These electronic circuits can execute computer-readable program instructions to implement various aspects of this application.

[0093] In some embodiments, the disclosed method may be implemented as computer program instructions encoded in a machine-readable format on a computer-readable storage medium or on other non-transitory media or articles of art. Figure 8A conceptual partial view schematically illustrates an example computer program product arranged according to at least some embodiments shown herein, the example computer program product including a computer program for executing computer processes on a computing device. In one embodiment, the example computer program product 800 is provided using a signal carrying medium 801. The signal carrying medium 801 may include one or more program instructions 802 that, when executed by one or more processors, can provide the above-described instructions for… Figure 1 The described function or part of the function. In addition... Figure 8 The program instruction 802 in the document also describes example instructions.

[0094] In some examples, the signal-bearing medium 801 may comprise a computer-readable medium 803, such as, but not limited to, a hard disk drive, a compact disc (CD), a digital video optical disc (DVD), a digital magnetic tape, a memory, read-only memory (ROM), or random access memory (RAM), etc. In some embodiments, the signal-bearing medium 801 may comprise a computer-recordable medium 804, such as, but not limited to, a memory, a read / write (R / W) CD, a R / W DVD, etc. In some embodiments, the signal-bearing medium 801 may comprise a communication medium 805, such as, but not limited to, digital and / or analog communication media (e.g., fiber optic cables, waveguides, wired communication links, wireless communication links, etc.). Therefore, for example, the signal-bearing medium 801 may be conveyed by a wireless communication medium 805 (e.g., a wireless communication medium conforming to the IEEE 802.11 standard or other transmission protocols). One or more program instructions 802 may be, for example, computer-executable instructions or logical implementation instructions. In some examples, such as for... Figure 2 The computing device described herein can be configured to provide various operations, functions, or actions in response to program instructions 802 transmitted to the computing device via one or more of a computer-readable medium 803, a computer-recordable medium 804, and / or a communication medium 805. It should be understood that the arrangements described herein are merely for illustrative purposes. Therefore, those skilled in the art will understand that other arrangements and other elements (e.g., machines, interfaces, functions, sequences, and functional groups, etc.) can be used instead, and some elements can be omitted depending on the desired result. Furthermore, many of the described elements are functional entities that can be implemented as discrete or distributed components, or implemented in combination with other components in any suitable combination and location.

[0095] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved.

[0096] It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, can be implemented using hardware (such as circuits or ASICs (Application Specific Integrated Circuits)) that performs the corresponding function or action, or using a combination of hardware and software, such as firmware.

[0097] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, disclosure, and appended claims in carrying out the claimed invention. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0098] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. An object detection method, characterized in that, include: Obtain the tabletop image; Determine the detection contour line of the tabletop and the contour line of the object on the tabletop in the tabletop image; If it is determined that the detection contour line of the platform is tangent to and / or intersects with the contour line of the object, the duration of the tangency and / or intersection is determined. If the duration is greater than or equal to a preset duration threshold, it is determined that there is a tendency for an object to fall from the table. After determining the detection contour lines of the tabletop and the contour lines of the objects on the tabletop in the tabletop image, the method further includes: Determine the vertical angle between the camera device used to capture the image of the tabletop and the target object; If the vertical angle is determined to be greater than the preset angle, the height of the target object, the contact point on the contact surface between the target object and the table that is closest to the detection contour line, and the distance between the contact point and the detection contour line are obtained. Based on the height and the distance, determine whether the vertical projection of the object on the table exceeds the detection contour line; If the vertical projection is determined to exceed the detection contour line, it is determined that the object has a tendency to fall.

2. The method according to claim 1, characterized in that, Determining the detection contour line of the tabletop in the tabletop image includes: Determine the outline of the tabletop in the tabletop image; The contour line on the other side, which is lower than the platform, is used as the detection contour line of the platform.

3. The method according to claim 1, characterized in that, The acquisition of the tabletop image includes: Acquire an image of the environment to be detected; Image recognition is performed on the image of the environment to be detected to obtain the tabletop image.

4. The method according to claim 1, characterized in that, After determining that there is a tendency for an object to fall onto the platform, the method further includes: Issue an alarm message.

5. An object detection device, characterized in that, include: The image acquisition module is used to acquire images of the tabletop. The contour line determination module is used to determine the detected contour line of the tabletop and the contour line of the object on the tabletop in the tabletop image; The falling trend determination module is used to determine the duration of the tangency and / or intersection when it is determined that the detection contour line of the platform is tangent to and / or intersects with the contour line of the object. If the duration is greater than or equal to a preset duration threshold, it is determined that there is a tendency for an object to fall from the table. The falling trend determination module is further configured to determine the vertical angle between the camera device used to capture the image of the tabletop and the target object; if the vertical angle is determined to be greater than a preset angle, the module acquires the height of the target object, the contact point on the contact surface between the target object and the tabletop that is closest to the detection contour line, and the distance between the contact point and the detection contour line; based on the height and the distance, the module determines whether the vertical projection of the object on the tabletop exceeds the detection contour line; if the vertical projection exceeds the detection contour line, the module determines that the object has a falling trend.

6. A camera device, comprising a lens assembly, an image sensor, a memory, and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method according to any one of claims 1-4.

7. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1-4.

8. A computer program product, characterized in that, Includes computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the method described in any one of claims 1-4.

9. A chip, characterized in that, It includes at least one processor for running a computer program or computer instructions stored in a memory to perform the method described in any one of claims 1-4.

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