Nesting detection method and device, monitoring equipment and storage medium

Abstract

The invention discloses a nesting detection method and device, monitoring equipment and a storage medium. The method comprises the following steps: acquiring at least two target monitoring pictures acquired by the monitoring equipment within a preset time period; for each target monitoring picture in the at least two target monitoring pictures, determining an object region in a preset unconventional activity region of the target monitoring picture, and calculating a region ratio of the object region to the unconventional activity region; and judging whether the monitoring equipment is nested or not according to the area proportion. Through the scheme, on the premise that the hardware maintenance cost of the monitoring equipment does not need to be increased, whether the monitoring equipment is nested or not can be accurately detected, so that linkage alarm can be performed when it is determined that the monitoring equipment is nested, the service life of the monitoring equipment is prolonged, and the effectiveness of a monitoring picture is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring devices, and in particular, to a nest building detection method, device, monitoring device, and storage medium. Background Art

[0002] Due to the particularity of the installation environment of outdoor monitoring devices, heat is generated during the operation of the monitoring devices, resulting in the heating of the body of the monitoring devices. In addition, the bodies of some monitoring devices, such as binocular cameras or large dome cameras, are relatively large, making them easy targets for birds to build nests, which will affect the lifespan and lenses of the monitoring devices.

[0003] In the related art, a hardware device can be added to the monitoring device to reduce the nest-building area, thereby trying to drive away birds from building nests. However, this will increase the production cost and maintenance cost of the monitoring device. Summary of the Invention

[0004] The present invention provides a nest building detection method, device, monitoring device, and storage medium, which can accurately detect whether a monitoring device is built with a nest without increasing the hardware maintenance cost of the monitoring device.

[0005] According to one aspect of the present invention, there is provided a nest building detection method, which is applied to a monitoring device. The method includes:

[0006] Obtaining at least two target monitoring images collected by the monitoring device within a preset time period;

[0007] For each of the at least two target monitoring images, determining an object area within a preset unconventional activity area of the target monitoring image, and calculating a ratio of the object area to the unconventional activity area;

[0008] Judging whether the monitoring device is built with a nest according to the ratio.

[0009] According to another aspect of the present invention, there is provided a nest building detection device, which is applied to a monitoring device. The device includes:

[0010] A target monitoring image acquisition module, configured to obtain at least two target monitoring images collected by the monitoring device within a preset time period;

[0011] A ratio calculation module, configured to, for each of the at least two target monitoring images, determine an object area within a preset unconventional activity area of the target monitoring image, and calculate a ratio of the object area to the unconventional activity area;

[0012] A nest building detection module, configured to judge whether the monitoring device is built with a nest according to the ratio.

[0013] According to another aspect of the present invention, there is provided a monitoring device, which includes:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the nest detection method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the nest detection method according to any embodiment of the present invention when executed.

[0018] In the nest detection solution of the embodiments of the present invention, at least two target monitoring images collected by the monitoring device within a preset time period are obtained; for each of the at least two target monitoring images, an object area within a preset unconventional activity area of the target monitoring image is determined, and the area ratio of the object area to the unconventional activity area is calculated; it is determined whether the monitoring device is nested according to the area ratio. Through the technical solution provided by the embodiments of the present invention, without increasing the hardware maintenance cost of the monitoring device, it is possible to accurately detect whether the monitoring device is nested, which helps to perform linkage alarms when it is determined that the monitoring device is nested, and improves the service life of the monitoring device and the effectiveness of the monitoring images.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 is a flowchart of a nest detection method according to Embodiment 1 of the present invention;

[0022] Figure 2aSchematic diagram of the display effect of a moving target on the monitoring screen of a monitoring device provided by an embodiment of the present invention;

[0023] Figure 2b Schematic diagram of the effect of a preset unconventional activity area provided by an embodiment of the present invention;

[0024] Figure 3 Flowchart of a nest building detection method provided by Embodiment II of the present invention;

[0025] Figure 4 Schematic structural diagram of a nest building detection device provided by Embodiment III of the present invention;

[0026] Figure 5 Schematic structural diagram of a monitoring device for implementing the nest building detection method of the embodiment of the present invention. Detailed implementation manners

[0027] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment I

[0030] Figure 1 A flowchart of a nest building detection method is provided for Embodiment I of the present invention. This embodiment is applicable to the situation of detecting whether a monitoring device is nested. This method can be executed by a nest building detection device, which can be implemented in the form of hardware and / or software, and the nest building detection device can be configured in the monitoring device. As Figure 1 shown, the method includes:

[0031] S110. Obtain at least two target surveillance images collected by a surveillance device within a preset time period.

[0032] In an embodiment of the present invention, at least two target surveillance images collected by a surveillance device within a preset time period can be obtained in real time, or at least two target surveillance images collected by the surveillance device within the preset time period can be obtained in response to the triggering of a nesting detection event. Exemplarily, when a nesting detection instruction input by a user is received, it can be determined that the nesting detection event is triggered. For another example, a nesting detection period of the surveillance device can be set to detect in real time whether the surveillance device reaches the nesting detection moment. If so, it is determined that the nesting detection event is triggered. For yet another example, when the surveillance device cannot collect effective surveillance images for a long time due to occlusion, it can be determined that the nesting detection event is triggered. In an embodiment of the present invention, when it is determined that the nesting detection event is triggered, at least two target surveillance images collected by the surveillance device within the preset time period are obtained, where the preset time period can be 8 hours, or one day, or two days, and the embodiment of the present invention does not limit the length of the preset time period. For another example, since the surveillance device needs to be detected for nesting in real time since it is installed in the surveillance scenario, at least two target surveillance images collected by the surveillance device within the preset time period are obtained in real time.

[0033] S120. For each of the at least two target surveillance images, determine an object area within a preset unconventional activity area of the target surveillance image, and calculate a ratio of the object area to the unconventional activity area.

[0034] Among them, the preset unconventional activity area is an area in the surveillance image of the surveillance device where moving objects such as vehicles and people do not appear. Since the sizes of the surveillance images collected by the surveillance device are the same, and the position areas of conventional moving objects such as vehicles and people in the surveillance image are relatively fixed, such as in the middle and lower areas of the surveillance image, the preset unconventional activity area can be determined according to the conventional activity area of the moving object in the surveillance image of the surveillance device. For example, the upper 1 / 3 area of the surveillance image is used as the preset unconventional activity area.

[0035] In an embodiment of the present invention, for each of the at least two target surveillance images, detect whether there is an object in the preset unconventional activity area of the target surveillance image. If so, determine the object area within the preset unconventional activity area of the target surveillance image, where the object area is the position area where the object is located within the preset unconventional activity area of the target surveillance image. The object can be any object, and the present invention does not limit the category of the object. It should be noted that the object area can be one or multiple. When there are multiple object areas, the sizes and shapes of the respective object areas can be the same or different, and the embodiment of the present invention does not limit the number, size, and shape of the object areas.

[0036] Calculate the area ratio of the object area within the preset unconventional activity area in each target monitoring image to the area of the preset unconventional activity area, where the area ratio is the ratio of the area of the object area to the area of the preset unconventional activity area. The larger the area ratio, the larger the area occupied by the objects contained in the preset unconventional activity area of the target monitoring image. Conversely, the smaller the area ratio, the smaller the area occupied by the objects contained in the preset unconventional activity area of the target monitoring image. Exemplarily, the monitoring device acquires 10 target monitoring images within a preset time period, and the area ratios corresponding to the 10 target monitoring images can be: 10%, 5%, 1%, 20%, 40%, 50%, 80%, 20%, 30%, and 70% respectively.

[0037] S130. Determine whether the monitoring device is nested according to the area ratio.

[0038] In the embodiment of the present invention, it is determined whether the monitoring device is nested according to the area ratio. For example, when the ratio of the first area ratio greater than the preset area ratio threshold to the second area ratio less than the preset area ratio threshold is greater than the preset threshold, it can be determined that the monitoring device is nested. Optionally, determining whether the monitoring device is nested according to the area ratio includes: counting the number of target monitoring images in which the area ratio is greater than the preset area ratio threshold among the at least two target monitoring images; determining whether the monitoring device is nested according to the number of target monitoring images. For example, if the preset area ratio threshold is 50%, then count the number of target monitoring images with an area ratio greater than 50% from at least two target monitoring images, and determine whether the monitoring device is nested according to the number of target monitoring images.

[0039] Optionally, determining whether the monitoring device is nested according to the number of target monitoring images includes: if the number of target monitoring images is greater than a preset number threshold, determining that the monitoring device is nested; wherein, the preset number threshold is directly proportional to the length of the preset time period. Exemplarily, determining whether the number of target monitoring images with a determination area ratio greater than 50% is greater than a preset number threshold (such as 10). If so, it is determined that the monitoring device is nested. It can be understood that if among the target monitoring images collected in the preset time period, there are more than 10 target monitoring images in which the object area of the preset non-conventional activity area is greater than 50% of the area of the preset non-conventional activity area, it indicates that a bird stands on the monitoring device, pecks at the lens of the monitoring device, or repeatedly flies in and out. Therefore, it can be determined that the monitoring device is nested. Among them, the preset number threshold is directly proportional to the length of the preset time period, that is, the longer the preset time period, the larger the preset number threshold. Conversely, the shorter the preset time period, the smaller the preset number threshold. For example, if the preset time period is 24 hours, the preset number threshold is 12; if the preset time period is 8 hours, the preset number threshold is 4. It can be understood that if among the target monitoring images collected in 24 hours, there are more than 12 target monitoring images in which the object area of the preset non-conventional activity area is greater than 50% of the area of the preset non-conventional activity area, it can be determined that the monitoring device is nested. If among the target monitoring images collected in 8 hours, there are more than 4 target monitoring images in which the object area of the preset non-conventional activity area is greater than 50% of the area of the preset non-conventional activity area, it can be determined that the monitoring device is nested.

[0040] Optionally, determining whether the monitoring device is nested according to the number of target monitoring images includes: calculating the ratio of the number of target monitoring images to the total number of target monitoring images collected within the preset time period; if the ratio is greater than a preset ratio threshold, determining that the monitoring device is nested. Exemplarily, calculating the ratio of the number of target monitoring images with a determination area ratio greater than 50% to the total number of target monitoring images collected within the preset time period. If the ratio is greater than the preset ratio threshold, it indicates that a bird stands on the monitoring device, pecks at the lens of the monitoring device, or repeatedly flies in and out. Therefore, it can be determined that the monitoring device is nested.

[0041] Optionally, when it is determined that the monitoring device is nested, an alarm prompt can be given so that the management personnel of the monitoring device can handle the nesting on the monitoring device, reduce the possibility of damage to the monitoring device, and improve the service life of the monitoring device.

[0042] The nest-building detection method according to the embodiments of the present invention obtains at least two target monitoring images collected by the monitoring device within a preset time period; for each of the at least two target monitoring images, determines an object area within a preset non-conventional activity area of the target monitoring image, and calculates a ratio of the object area to the non-conventional activity area; and determines whether the monitoring device is nested according to the ratio. Through the technical solution provided by the embodiments of the present invention, without increasing the hardware maintenance cost of the monitoring device, it is possible to accurately detect whether the monitoring device is nested, which helps to perform linkage alarm when it is determined that the monitoring device is nested, and improves the service life of the monitoring device and the effectiveness of the monitoring images.

[0043] In some embodiments, before determining the object area within the preset non-conventional activity area of the target monitoring image for each of the at least two target monitoring images, it further includes: obtaining at least two historical monitoring images collected by the monitoring device; respectively performing moving target detection on the at least two historical monitoring images, and determining a target position area where the moving target is located in the at least two historical monitoring images; and determining the preset non-conventional activity area of the monitoring image of the monitoring device according to the target position area.

[0044] Exemplarily, when the monitoring device monitors a target scene, the upper area of the collected monitoring image usually captures a bit of the sky, and conventional moving targets such as vehicles and people usually appear in the lower-middle area of the monitoring image. In the embodiments of the present invention, in order to detect whether the monitoring device is nested, the conventional activity area and the non-conventional activity area of the monitoring image of the monitoring device can be determined in advance, where the conventional activity area is the position area where moving targets such as vehicles and people are located in the monitoring image, and the non-conventional activity area can be understood as the position area where other objects except moving targets such as vehicles and people are located in the monitoring image. Obtain at least two historical monitoring images collected by the monitoring device, and respectively perform moving target detection on the at least two historical monitoring images based on a target detection algorithm, where the moving targets may include vehicles and people. Exemplarily, Figure 2a is a schematic diagram of the display effect of the moving target in the monitoring image of the monitoring device provided by the embodiments of the present invention. Determine the target position area where the moving target is located in the at least two historical monitoring images, and the preset non-conventional activity area of the monitoring image of the monitoring device can be determined according to the target position area.

[0045] Optionally, determining the preset unconventional activity area of the monitoring screen of the monitoring device according to the target position area includes: determining the conventional activity area of the monitoring screen of the monitoring device according to the target position area; using the area of the monitoring screen of the monitoring device other than the conventional activity area as the preset unconventional activity area. For example, taking the sum of all target position areas in the monitoring screen of the monitoring device as the conventional activity area, and using the area of the monitoring screen of the monitoring device other than the conventional activity area as the preset unconventional activity area. Another example is to determine the overlapping area between the upper area of the 1 / 2 horizontal dividing line of the monitoring screen of the monitoring device and the conventional activity area, and using the other area in the upper area of the 1 / 2 horizontal dividing line of the monitoring screen except the overlapping area as the preset unconventional activity area. Exemplarily, Figure 2b is a schematic diagram of the effect of a preset unconventional activity area provided by an embodiment of the present invention.

[0046] Optionally, after using the area of the monitoring screen of the monitoring device other than the conventional activity area as the preset unconventional activity area, it further includes: detecting whether there are birds in the preset surrounding area of the preset unconventional activity area of the at least two historical monitoring screens, and if so, correcting the preset unconventional activity area according to the preset surrounding area. Exemplarily, for each historical monitoring screen in the at least two historical monitoring screens, based on the target detection algorithm, it is determined whether there are birds in the preset surrounding area of the preset unconventional activity area of the historical monitoring screen, and if so, the preset unconventional activity area is corrected according to the preset surrounding area. For example, the preset surrounding area may include a preset edge area close to the unconventional activity area and / or a preset intermediate area centered on the central axis of the unconventional activity area. When there are birds in the preset surrounding area, the preset surrounding area is also divided into the preset unconventional activity area to correct the original preset unconventional activity area. The advantage of such a setting is that the preset unconventional activity area in the monitoring screen of the monitoring device can be accurately determined, which helps to improve the accuracy of detecting whether the monitoring device is nested.

[0047] Embodiment 2

[0048] Figure 3 is a flowchart of a nest detection method provided by Embodiment 2 of the present invention, as Figure 3 shown, the method includes:

[0049] S310. Obtain at least two historical monitoring screens collected by the monitoring device.

[0050] S320. Perform moving target detection on at least two historical monitoring screens respectively, and determine the target position area where the moving target is located in the at least two historical monitoring screens.

[0051] S330. Determine the regular activity area of the monitoring screen of the monitoring device according to the target location area.

[0052] S340. Take the area outside the regular activity area in the monitoring screen of the monitoring device as the preset irregular activity area.

[0053] S350. Obtain at least two target monitoring screens collected by the monitoring device within the preset time period.

[0054] S360. For each of the at least two target monitoring screens, determine the object area within the preset irregular activity area of the target monitoring screen, and calculate the area ratio of the object area to the irregular activity area.

[0055] S370. Count the number of target monitoring screens in which the area ratio is greater than the preset area ratio threshold among the at least two target monitoring screens.

[0056] S380. Determine whether the number of target monitoring screens is greater than the preset number threshold, where the preset number threshold is directly proportional to the length of the preset time period. If so, execute S390; otherwise, execute S3100.

[0057] S390. Determine that the monitoring device is nested.

[0058] S3100. Determine that the monitoring device is not nested.

[0059] The nesting detection method of the embodiment of the present invention can accurately detect whether the monitoring device is nested without increasing the hardware maintenance cost of the monitoring device, which helps to perform linkage alarm when it is determined that the monitoring device is nested, and improves the service life of the monitoring device and the effectiveness of the monitoring screen.

[0060] Embodiment III

[0061] Figure 4 It is a schematic structural diagram of a nesting detection device provided by Embodiment III of the present invention. As Figure 4 shown, the device includes:

[0062] A target monitoring screen acquisition module 410, configured to obtain at least two target monitoring screens collected by the monitoring device within the preset time period;

[0063] An area ratio calculation module 420, configured to, for each of the at least two target monitoring screens, determine the object area within the preset irregular activity area of the target monitoring screen, and calculate the area ratio of the object area to the irregular activity area;

[0064] A nesting detection module 430, configured to determine whether the monitoring device is nested according to the area ratio.

[0065] Optionally, the nesting detection module includes:

[0066] A target monitoring screen quantity statistics unit, configured to count the quantity of target monitoring screens in which the proportion of the region is greater than a preset region proportion threshold value among the at least two target monitoring screens;

[0067] A nesting judgment unit, configured to judge whether the monitoring device is nested according to the quantity of the target monitoring screens.

[0068] Optionally, the nesting judgment unit is configured to:

[0069] If the quantity of the target monitoring screens is greater than a preset quantity threshold value, it is determined that the monitoring device is nested; wherein, the preset quantity threshold value is in direct proportion to the length of the preset time period.

[0070] Optionally, the nesting judgment unit is configured to:

[0071] Calculate the ratio of the quantity of the target monitoring screens to the total quantity of the target monitoring screens collected within the preset time period;

[0072] If the ratio is greater than a preset ratio threshold value, it is determined that the monitoring device is nested.

[0073] Optionally, it further includes:

[0074] A historical monitoring screen acquisition module, configured to acquire at least two historical monitoring screens collected by the monitoring device before determining the object region within the preset unconventional activity region of each of the at least two target monitoring screens;

[0075] A target position region determination module, configured to perform moving target detection on each of the at least two historical monitoring screens respectively, and determine the target position region where the moving target is located in the at least two historical monitoring screens;

[0076] A preset unconventional activity region determination module, configured to determine the preset unconventional activity region of the monitoring screen of the monitoring device according to the target position region.

[0077] Optionally, the preset unconventional activity region determination module is configured to:

[0078] Determine the conventional activity region of the monitoring screen of the monitoring device according to the target position region;

[0079] Use the region other than the conventional activity region in the monitoring screen of the monitoring device as the preset unconventional activity region.

[0080] Optionally, the device further includes:

[0081] An unconventional activity area correction module is configured to, after taking the area other than the regular activity area in the monitoring screen of the monitoring device as the preset unconventional activity area, detect whether there are birds in the preset surrounding area of the preset unconventional activity area in the at least two historical monitoring screens. If so, correct the preset unconventional activity area according to the preset surrounding area.

[0082] The nesting detection device provided by the embodiments of the present invention can execute the nesting detection method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0083] Embodiment 4

[0084] Figure 5 FIG. shows a schematic structural diagram of a monitoring device 10 that can be used to implement the embodiments of the present invention. The monitoring device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The monitoring device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0085] As Figure 5 shown, the monitoring device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the monitoring device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0086] Multiple components in the monitoring device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the monitoring device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0087] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the nesting detection method.

[0088] In some embodiments, the nesting detection method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the monitoring device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the nesting detection method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the nesting detection method by any other suitable means (e.g., by means of firmware).

[0089] The various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, the programmable processor can be a special or general programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0090] A computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0091] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0092] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a monitoring device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the monitoring device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0093] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0094] A computing system can include a client and a server. The client and the server are generally remote from each other and typically interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0095] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and this is not limited herein.

[0096] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A nest detection method, characterized in that, Applied to a monitoring device, the method includes: Obtaining at least two target monitoring images collected by the monitoring device within a preset time period; For each of the at least two target monitoring images, determining an object area within a preset unconventional activity area of the target monitoring image, and calculating a ratio of the object area to the unconventional activity area; Judging whether the monitoring device is nested according to the ratio; 2. The method according to claim 1, characterized in that, Judging whether the monitoring device is nested according to the ratio includes: Counting the number of target monitoring images in the at least two target monitoring images whose ratio is greater than a preset ratio threshold; Judging whether the monitoring device is nested according to the number of target monitoring images; 3. The method according to claim 2, characterized in that, Judging whether the monitoring device is nested according to the number of target monitoring images includes: If the number of target monitoring images is greater than a preset number threshold, determining that the monitoring device is nested; wherein, the preset number threshold is directly proportional to the length of the preset time period.

4. The method according to claim 2, characterized in that, Judging whether the monitoring device is nested according to the number of target monitoring images includes: Calculating a ratio of the number of target monitoring images to the total number of target monitoring images collected within the preset time period; If the ratio is greater than a preset ratio threshold, determining that the monitoring device is nested.

5. The method according to claim 1, characterized in that, Before determining, for each of the at least two target monitoring images, an object area within a preset unconventional activity area of the target monitoring image, it further includes: Obtaining at least two historical monitoring images collected by the monitoring device; Performing moving target detection on each of the at least two historical monitoring images respectively to determine a target position area where the moving target is located in the at least two historical monitoring images; Determining the preset unconventional activity area of the monitoring image of the monitoring device according to the target position area; 6. The method according to claim 5, characterized in that, Determining the preset unconventional activity area of the monitoring image of the monitoring device according to the target position area includes: Determining a conventional activity area of the monitoring image of the monitoring device according to the target position area; Taking an area other than the conventional activity area in the monitoring image of the monitoring device as the preset unconventional activity area.

7. The method according to claim 5, characterized in that, After taking an area other than the conventional activity area in the monitoring image of the monitoring device as the preset unconventional activity area, it further includes: Detecting whether there are birds in a preset surrounding area of the preset unconventional activity area of the at least two historical monitoring images, and if so, correcting the preset unconventional activity area according to the preset surrounding area.

8. A nest detection device, characterized in that, Applied to a monitoring device, the device includes: A target monitoring image acquisition module, configured to obtain at least two target monitoring images collected by the monitoring device within a preset time period; A ratio calculation module, configured to, for each of the at least two target monitoring images, determine an object area within a preset unconventional activity area of the target monitoring image, and calculate a ratio of the object area to the unconventional activity area; A nesting detection module, configured to judge whether the monitoring device is nested according to the ratio.

9. A monitoring device, characterized in that, The monitoring device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the nesting detection method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for implementing the nesting detection method according to any one of claims 1-7 when the computer instructions are executed by a processor.

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