Equipment motion control method and device, electronic equipment and computer storage medium

Abstract

The invention provides an equipment motion control method and device, electronic equipment and a computer storage medium, and the method comprises the steps: calculating a weight matrix of a historical event, the historical event being a monitoring image detection event on first image collection equipment; determining a candidate area according to the weight matrix; generating a planning path based on the candidate area, and generating a corresponding motion instruction; and controlling the second image acquisition device to execute a corresponding action through the motion instruction, wherein the image acquisition range of the second image acquisition device is smaller than that of the first image acquisition device. According to the method, the weight of each area is dynamically determined according to the historical event, the motion instruction of the second image acquisition equipment is determined, and then the second image acquisition equipment is controlled to move to the corresponding area for monitoring, so that the intelligent scheduling of the second image acquisition equipment is realized, the monitoring efficiency is improved, and the invalid monitoring time is shortened.

Description

Technical Field

[0001] The present application relates to the field of automatic control, and in particular to a method and apparatus for controlling equipment motion, an electronic device, and a computer storage medium. Background Art

[0002] In today's era of information explosion and security first, wide-angle cameras are the "eyes in the sky" that protect the peace of the city, and their importance is self-evident. Unfortunately, however, these devices, which should have been the backbone of the intelligent security system, are often unable to do their job due to technical limitations. Therefore, it is usually necessary to cooperate with image acquisition devices with a smaller image acquisition range to obtain accurate monitoring information.

[0003] Although wide-angle cameras perform well in wide-angle monitoring, a fixed or simple loop method is generally used to control image acquisition equipment. This control method lacks flexibility and is difficult to perform intelligent scheduling based on actual monitoring needs. Summary of the invention

[0004] In view of this, the purpose of the embodiments of the present application is to provide a device motion control method, apparatus, electronic device and computer storage medium, which can realize intelligent scheduling of image acquisition equipment.

[0005] In a first aspect, an embodiment of the present application provides a method for controlling device motion, comprising: calculating a weight matrix of historical events, wherein the historical events are monitoring screen detection events on a first image acquisition device; determining a candidate area according to the weight matrix; generating a planned path based on the candidate area, and generating corresponding motion instructions; controlling a second image acquisition device to perform corresponding actions through the motion instructions, the image acquisition range of the second image acquisition device being smaller than the image acquisition range of the first image acquisition device.

[0006] In the above implementation process, by dynamically determining the weight of each area according to historical events and determining the movement instructions of the second image acquisition device, and then controlling the second image acquisition device to move to the corresponding area for monitoring, intelligent scheduling of the second image acquisition device is achieved, monitoring efficiency is improved, and invalid monitoring time is reduced.

[0007] In one embodiment, the calculation of the weight matrix of historical events includes: calculating the weight growth function of each area; calculating the weight distribution matrix of each historical event in the current time and current latitude area according to the weight growth function; and updating the weight matrix through the weight distribution matrix.

[0008] In the above implementation process, by calculating the weight distribution matrix of each historical event in the current time and current dimension area in real time, and updating the weight matrix through the weight distribution matrix, the latest weight matrix can be obtained in real time, which can improve the real-time and security of the weight matrix.

[0009] In one embodiment, updating the weight matrix through the weight distribution matrix includes: for the area covered by the second image acquisition device in the previous round, setting the weight growth to 0; for the area not covered by the second image acquisition device in the previous round, updating the weight matrix according to the weight distribution matrix.

[0010] In the above implementation process, corresponding processing methods are adopted for weight matrices of different areas according to the monitoring situation of the second image acquisition device in the previous round, thereby improving the accuracy of the weight matrix.

[0011] In one embodiment, determining the candidate area based on the weight matrix includes: filtering the weight matrix by setting a threshold; performing a connected domain analysis on the filtered weight matrix; classifying adjacent pixels that meet the conditions into the same connected domain to obtain one or more connected domains; and determining the candidate area based on the connected domain.

[0012] In the above implementation process, by filtering the weight matrix according to the set threshold, the weight matrix with lower weight can be filtered out, so that the remaining weight matrices are all matrices with relatively high weight ratios, thereby improving the accuracy of the connected area.

[0013] In one embodiment, determining the candidate region according to the connected domain includes: calculating a connected domain area of ​​each connected domain; and determining a connected domain whose area is greater than or equal to an area threshold as the candidate region.

[0014] In the above implementation process, the area threshold is used to filter out some connected domains whose area is smaller than the area threshold, and the filtered connected domains are used as candidate areas. This can avoid the second image acquisition device from monitoring some areas that do not need to be monitored, reduce invalid monitoring, and improve monitoring accuracy.

[0015] In one embodiment, generating a planned path based on the candidate areas includes: setting the current position of the second image acquisition device as the initial position; setting all candidate areas to an "unvisited" state; selecting a candidate area closest to the initial position from all "unvisited" candidate areas, and marking the nearest candidate area as "visited"; adding the nearest candidate area to a path list; selecting a candidate area closest to the initial position from all "unvisited" candidate areas and repeating until all candidate areas are visited.

[0016] In the above implementation process, by adopting the nearest neighbor algorithm to plan the path of the second image acquisition device, the moving distance of the second image acquisition device can be minimized and the control efficiency and monitoring efficiency of the second image acquisition device can be improved.

[0017] In one embodiment, the generating of corresponding motion instructions includes: decomposing the path list into a series of target points respectively; generating corresponding control instructions for each target point, wherein the control instructions include horizontal angle, vertical angle, moving speed and moving acceleration; calculating the time required from the current point to the next target point, and allocating execution time for each control instruction; and sorting each control instruction in sequence according to the path order to form a complete motion instruction.

[0018] In the above implementation process, by decomposing the path list into a series of target points, generating corresponding control instructions for each target point, and calculating the time required to move between adjacent target points, accurate motion instructions for controlling the movement of the second image acquisition device can be generated, thereby improving the accuracy of control of the second image acquisition device.

[0019] In the second aspect, an embodiment of the present application also provides a device motion control apparatus, comprising: a calculation module, used to calculate a weight matrix of historical events, wherein the historical events are monitoring screen detection events on a first image acquisition device; a determination module, used to determine a candidate area according to the weight matrix; a generation module, used to generate a planned path based on the candidate area, and generate corresponding motion instructions; and a control module, used to control the second image acquisition device to perform corresponding actions through the motion instructions.

[0020] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of the method in the above-mentioned first aspect, or any possible implementation of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the device motion control method in the above-mentioned first aspect, or any possible implementation of the first aspect are executed.

[0022] In order to make the above-mentioned objects, features and advantages of the present application more obvious and understandable, embodiments are given below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 A schematic diagram of the interaction between the first image acquisition device, the second image acquisition device and the electronic device provided in an embodiment of the present application;

[0025] Figure 2 A block diagram of an electronic device provided in an embodiment of the present application;

[0026] Figure 3 A flow chart of a device motion control method provided in an embodiment of the present application;

[0027] Figure 4 A schematic diagram of the functional modules of the device motion control apparatus provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings in the embodiments of the present application.

[0029] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0030] Wide-angle image acquisition devices (such as panoramic ball surveillance cameras) usually have a wider image acquisition field of view and can capture a wider range of scene information. When used in combination with image acquisition devices with a smaller acquisition range, the wide-angle image acquisition device can achieve more flexible and accurate monitoring by controlling the image acquisition device with a smaller acquisition range.

[0031] However, after long-term research, the inventors of the present application found that existing wide-angle image acquisition equipment usually adopts a fixed or simple cycle method to control image acquisition equipment with a smaller acquisition range, which makes it difficult to perform intelligent scheduling according to actual monitoring needs, resulting in low monitoring efficiency and a large amount of invalid monitoring time.

[0032] In view of this, the present application proposes a device motion control method, which dynamically determines the weight of each area according to historical events and determines the motion instructions of the second image acquisition device, and then controls the second image acquisition device to move to the corresponding area for monitoring, thereby realizing intelligent scheduling of the second image acquisition device, improving monitoring efficiency, and reducing invalid monitoring time.

[0033] To facilitate understanding of this embodiment, the operating environment of a device motion control method disclosed in an embodiment of the present application is first introduced in detail.

[0034] like Figure 1 As shown, it is a schematic diagram of the interaction between the first image acquisition device, the second image acquisition device and the electronic device provided in the embodiment of the present application. The electronic device is connected to one or more first image acquisition devices and second image acquisition devices through a network to communicate or interact with data. The electronic device can be a network server, a database server, etc., or a personal computer (PC), a tablet computer, a smart phone, a personal digital assistant (PDA), etc. The electronic device can be selected according to the actual situation.

[0035] The first image acquisition device and the second image acquisition device are both devices for image acquisition, such as panoramic balls, pan / tilt heads, cameras, and skynets.

[0036] The image acquisition range of the second image acquisition device is smaller than the image acquisition range of the first image acquisition device. For example, the first image acquisition device is a panoramic ball, and the second image acquisition device is a pan / tilt head. For another example, the first image acquisition device is a camera with a field of view of 270°, and the second image acquisition device is a camera with a field of view of 180°. The first image acquisition device and the second image acquisition device can be selected according to actual conditions.

[0037] The first image acquisition device and the second image acquisition device are both connected to an electronic device, wherein the electronic device is configured to determine a motion control instruction of the second image acquisition device according to the image information transmitted by the first image acquisition device, and control the motion of the second image acquisition device based on the motion control instruction.

[0038] To facilitate understanding of this embodiment, first, an electronic device that executes the device motion control method disclosed in the embodiment of the present application is introduced in detail.

[0039] like Figure 2 , which is a block diagram of an electronic device. The electronic device 100 may include a memory 111 and a processor 113. A person skilled in the art may understand that Figure 2The structure shown is only for illustration and does not limit the structure of the electronic device 100. For example, the electronic device 100 may further include Figure 2 More or fewer components as shown, or with Figure 2 Different configurations are shown.

[0040] The memory 111 and the processor 113 are directly or indirectly electrically connected to each other to achieve data transmission or interaction. For example, these elements can be electrically connected to each other via one or more communication buses or signal lines. The processor 113 is used to execute the executable module stored in the memory.

[0041] The memory 111 may be, but not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc. The memory 111 is used to store programs, and the processor 113 executes the program after receiving the execution instruction. The method executed by the electronic device 100 defined by the process disclosed in any embodiment of the present application can be applied to the processor 113, or implemented by the processor 113.

[0042] The processor 113 may be an integrated circuit chip with signal processing capability. The processor 113 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0043] The electronic device 100 in this embodiment can be used to execute each step in each method provided in the embodiments of the present application. The implementation process of the device motion control method is described in detail below through several embodiments.

[0044] See also Figure 3 , is a flow chart of the device motion control method provided by the embodiment of the present application. Figure 3 The specific process shown is described in detail.

[0045] Step S201, calculating the weight matrix of historical events.

[0046] The historical events are monitoring screen detection events on the first image acquisition device, such as human detection, motion detection, etc. The human detection result can be obtained through a target detection model, and the motion detection structure can be obtained by a motion detection algorithm.

[0047] The weight matrix here refers to an X*Y matrix, where the length X represents the longitude (-X1 to X1) on the first image acquisition device, and the width Y represents the dimension (-90 to 90) of the first image acquisition device. Each value on the matrix represents the accumulated weight of the historical event that occurred at that location. For example, if the first image acquisition device is a panoramic ball, the weight matrix is ​​a 360*180 matrix, where the length 360 represents the longitude (-180 to 180) on the first image acquisition device, and the width 180 represents the dimension (-90 to 90) of the first image acquisition device.

[0048] The first image acquisition device is a device for image acquisition, for example, a panoramic ball, a skynet, a surveillance camera, etc. The first image acquisition device can be selected according to actual conditions.

[0049] It is understandable that the first image acquisition device can acquire event information of a large range of the target area in real time. The event information can be used to construct a weight matrix of historical events.

[0050] Step S202, determining candidate regions according to the weight matrix.

[0051] The candidate area here refers to an area that may need to be controlled to move and monitor the second image acquisition device.

[0052] The image acquisition range of the second image acquisition device is smaller than that of the first image acquisition device, that is, the first image acquisition device is usually used to acquire image information in a larger range, and the second image acquisition device is used to acquire image information in a smaller range.

[0053] It should be understood that since the first image acquisition device needs to acquire image information of a large range, the clarity of the image acquired by the first image acquisition device is usually low. When the image surface in a certain area changes, it is necessary to further determine the specific situation of the change. At this time, the first image acquisition device may be difficult to meet the demand. By controlling the lens of the second image device to move to the area and acquiring the image information of the area based on the second image device, since the second image device can acquire a clearer image, the specific situation of the area can be further determined through the second image acquisition device.

[0054] It can be understood that since the weight matrix is ​​a weight matrix of historical events, the weight matrix can be used to determine which areas correspond to the images that may change, and then the areas where the images have changed can be used as candidate areas that may require further monitoring by the second image acquisition device.

[0055] Step S203: Generate a planned path based on the candidate area and generate corresponding motion instructions.

[0056] It should be understood that after the candidate area is determined, the second image acquisition device needs to be controlled to move to the corresponding candidate area. Therefore, a planned path can be generated according to the candidate area, and a corresponding motion instruction can be generated based on the planned path, and the second image acquisition device can be controlled to perform a corresponding action through the motion instruction.

[0057] The planning path here can be determined using the nearest neighbor algorithm.

[0058] Step S204: Control the second image acquisition device to perform corresponding actions through motion instructions.

[0059] Optionally, the motion instruction may include parameters such as the location of the target area (eg, longitude and latitude, angle), movement parameters (eg, speed, acceleration, etc.), and the motion instruction may be selected according to actual conditions.

[0060] In the above implementation process, by dynamically determining the weight of each area according to historical events and determining the movement instructions of the second image acquisition device, and then controlling the second image acquisition device to move to the corresponding area for monitoring, intelligent scheduling of the second image acquisition device is achieved, monitoring efficiency is improved, and invalid monitoring time is reduced.

[0061] In a possible implementation, step S201 includes: calculating a weight growth function for each region; calculating a weight distribution matrix for each historical event at the current time and the current latitude region according to the weight growth function; and updating the weight matrix through the weight distribution matrix.

[0062] In one embodiment, the weight growth function of each region may be determined by the following formula:

[0063]

[0064] Among them, δ is the weight growth factor, γi is the spatial weight factor, is the idle time of the area, is the weight growth function.

[0065] The spatial weight factor here may include weight factors of one or more regions such as a sky region, a horizon region, and an event region.

[0066] The above-mentioned spatial weight factor can be set in advance or determined in real time according to actual conditions (for example, determined in real time through an AI big model). The method for determining the spatial weight factor can be selected according to actual conditions.

[0067] The weight distribution matrix of each historical event at the current time and the current latitude area can be determined by the following formula:

[0068]

[0069] Among them, w is the cumulative impact weight of historical events in the current time and current dimension area, αi is the event type weight (such as the weight of motion detection and human detection events), β is the time decay factor (the larger the value, the faster the weight decays), t_current is the current time, ti is the time when the event occurred, and γi is the spatial weight factor. is the longitude of the event, θi is the latitude of the event, is the weight growth function.

[0070] It should be understood that after the weight matrix at each time is determined, the weight matrix can be updated according to the latest calculated weight distribution matrix, so that the weight matrix is ​​always the latest weight matrix.

[0071] In the above implementation process, by calculating the weight distribution matrix of each historical event in the current time and current dimension area in real time, and updating the weight matrix through the weight distribution matrix, the latest weight matrix can be obtained in real time, which can improve the real-time and security of the weight matrix.

[0072] In one possible implementation, the weight matrix is ​​updated through the weight distribution matrix, including: for the area covered by the second image acquisition device in the previous round, the weight growth is set to 0; for the area not covered by the second image acquisition device in the previous round, the weight matrix is ​​updated according to the weight distribution matrix.

[0073] It is understandable that for an area that has been monitored by the second image acquisition device in the previous round, the area may not be monitored in the next round to avoid repeated monitoring. Therefore, the weight growth of the area may be set to 0.

[0074] Similarly, in order to improve the comprehensiveness of monitoring, for areas that were not monitored by the second image acquisition device in the previous round, the weight matrix can be updated in real time to determine the candidate areas in real time, and then the second image acquisition device can be controlled to monitor.

[0075] In one embodiment, the update formula of the weight matrix may be:

[0076] W_new(x,y)=

[0077] {

[0078] 0, if the region (x,y) is covered

[0079] W_old(x,y)+δ×e^(γi×t_idle(x,y)), otherwise

[0080] }

[0081] In the above implementation process, corresponding processing methods are adopted for weight matrices of different areas according to the monitoring situation of the second image acquisition device in the previous round, thereby improving the accuracy of the weight matrix.

[0082] In a possible implementation, step S202 includes: filtering the weight matrix by setting a threshold; performing a connected domain analysis on the filtered weight matrix; classifying adjacent pixels that meet the conditions into the same connected domain to obtain one or more connected domains; and determining a candidate area based on the connected domain.

[0083] The set threshold here may be a weight threshold set in advance, and the set threshold is configured to filter out areas with a relatively small weight ratio.

[0084] Optionally, the connected domain analysis can be performed on the screened areas through algorithms such as breadth-first search and depth-first search.

[0085] Specifically, the connected domain can be realized by the following steps: initialize an empty connected domain list, traverse all pixels that meet the conditions, start BFS or DFS for unvisited pixels, mark all connected pixels as the same connected domain, and add them to the connected domain list.

[0086] In the above implementation process, by filtering the weight matrix according to the set threshold, the weight matrix with lower weight can be filtered out, so that the remaining weight matrices are all matrices with relatively high weight ratios, thereby improving the accuracy of the connected area.

[0087] In a possible implementation, determining the candidate region according to the connected domain includes: calculating the connected domain area of ​​each connected domain; and determining the connected domain whose connected domain area is greater than or equal to an area threshold as the candidate region.

[0088] The area threshold here can be set in advance, and the area threshold is the minimum area that needs to be monitored.

[0089] The area of ​​the connected domain mentioned above can be determined by calculating the number of pixels.

[0090] Understandably, in some cases, some areas may be caused by noise or accidental events, and these areas may not be areas that need to be monitored. By filtering out these areas according to the area threshold, the second image acquisition device can be prevented from monitoring some areas that do not need to be monitored, reducing invalid monitoring and improving monitoring accuracy.

[0091] The above-mentioned candidate area is the area that the second image acquisition device should cover.

[0092] In the above implementation process, the area threshold is used to filter out some connected domains whose area is smaller than the area threshold, and the filtered connected domains are used as candidate areas. This can avoid the second image acquisition device from monitoring some areas that do not need to be monitored, reduce invalid monitoring, and improve monitoring accuracy.

[0093] In one possible implementation, a planned path is generated based on candidate areas, including: setting the current position of the second image acquisition device as the initial position; setting all candidate areas to an "unvisited" state; selecting a candidate area closest to the initial position from all "unvisited" candidate areas, and marking the nearest candidate area as "visited"; adding the nearest candidate area to a path list; selecting a candidate area closest to the initial position from all "unvisited" candidate areas and repeating until all candidate areas are visited.

[0094] The path list here is used to store the area (ie, candidate area) that the second image acquisition device needs to access. When there are many candidate areas, multiple candidate areas can be stored in the path list, and then the second image acquisition device can be controlled to execute the corresponding path according to the candidate areas in the path list.

[0095] When adding the candidate areas to the path list, the candidate areas are added in sequence according to the distances between the candidate areas and the second image acquisition device from near to far.

[0096] In one embodiment, the planned path of the second image acquisition device may be a path of the candidate area stored in the path list.

[0097] Optionally, when determining the next path, in addition to considering the distance, the coordination of the horizontal and vertical movements of the second image acquisition device may also be considered to avoid abrupt movement of the second image acquisition device.

[0098] In another embodiment, the selection process may be optimized by using a weighted distance or introducing a motion smoothing factor.

[0099] In the above implementation process, by adopting the nearest neighbor algorithm to plan the path of the second image acquisition device, the moving distance of the second image acquisition device can be minimized and the control efficiency and monitoring efficiency of the second image acquisition device can be improved.

[0100] In one possible implementation, the corresponding motion instructions are generated, including: decomposing the path list into a series of target points; generating a corresponding control instruction for each target point; calculating the time required from the current point to the next target point, and allocating execution time for each control instruction; and sorting each control instruction in sequence according to the path order to form a complete motion instruction.

[0101] The control instructions include horizontal angle, vertical angle, moving speed, moving acceleration, etc. The control instructions can be selected according to actual conditions.

[0102] The time required from the current point to the next target point can be calculated based on the moving speed and acceleration.

[0103] In one embodiment, execution time may be allocated to each instruction to ensure continuity and synchronization between instructions.

[0104] It should be understood that after the motion instruction is completed, the motion instruction can be transmitted to the control module of the second image acquisition device, and the second image acquisition device performs corresponding actions according to the sequence of the motion instruction.

[0105] In one embodiment, if an abnormal situation occurs during the execution of the motion instruction by the second image acquisition device (e.g., the target point cannot be reached, the pan / tilt fails, etc.), the motion instruction is stopped or the instruction sequence is adjusted. In addition, the abnormal information can be recorded and fed back to step S201 to dynamically adjust the monitoring strategy.

[0106] The following is an example to illustrate the specific implementation process of the embodiment of the present application: If the first image acquisition device is a panoramic ball, and the second image acquisition device is a pan-tilt head. The control method of the pan-tilt head is: determine the weight matrix of the historical events based on the historical events acquired by the panoramic ball, calculate the weight distribution matrix of each historical event at the current time and the current longitude and latitude area, and update the weight matrix through the weight distribution matrix. Filter the weight matrix according to the set threshold, and perform a connected domain analysis on the filtered weight matrix, classify the pixels that meet the conditions and are adjacent into the same connected domain, and determine the connected domain as the preliminary candidate area. Filter out the candidate areas whose connected domain area is less than the area threshold to obtain the candidate area. Then, generate a planned path based on the candidate area, and generate corresponding motion instructions. Finally, transmit the motion instruction to the pan-tilt head, the pan-tilt head moves to the corresponding position according to the motion instruction, and monitors the area at the position.

[0107] In the above implementation process, by decomposing the path list into a series of target points, generating corresponding control instructions for each target point, and calculating the time required to move between adjacent target points, accurate motion instructions for controlling the movement of the second image acquisition device can be generated, thereby improving the accuracy of control of the second image acquisition device.

[0108] Based on the same application concept, an equipment motion control device corresponding to the equipment motion control method is also provided in the embodiment of the present application. Since the principle of solving the problem by the device in the embodiment of the present application is similar to that in the aforementioned equipment motion control method embodiment, the implementation of the device in this embodiment can refer to the description in the embodiment of the above method, and the repeated parts will not be repeated.

[0109] See also Figure 4 , is a functional module diagram of the device motion control device provided in the embodiment of the present application. Each module in the device motion control device in this embodiment is used to execute each step in the above method embodiment. The device motion control device includes a calculation module 501, a determination module 502, a generation module 503, and a control module 504; wherein,

[0110] The calculation module 501 is used to calculate the weight matrix of the historical event, where the historical event is a monitoring screen detection event on the first image acquisition device.

[0111] The determination module 502 is used to determine the candidate region according to the weight matrix.

[0112] The generation module 503 is used to generate a planned path based on the candidate area and generate corresponding motion instructions.

[0113] The control module 504 is used to control the second image acquisition device to perform corresponding actions through the motion instruction.

[0114] In a possible implementation, the calculation module 501 is further used to: calculate the weight growth function of each region; calculate the weight distribution matrix of each historical event in the current time and current latitude region according to the weight growth function; and update the weight matrix through the weight distribution matrix.

[0115] In a possible implementation, the calculation module 501 is specifically used to: set the weight growth to 0 for the area covered by the second image acquisition device in the previous round; and update the weight matrix according to the weight distribution matrix for the area not covered by the second image acquisition device in the previous round.

[0116] In a possible implementation, the determination module 502 is further used to: filter the weight matrix by setting a threshold; perform a connected domain analysis on the filtered weight matrix; classify adjacent pixel points that meet the conditions into the same connected domain to obtain one or more connected domains; and determine the candidate area based on the connected domain.

[0117] In a possible implementation manner, the determination module 502 is specifically configured to: calculate the connected domain area of ​​each of the connected domains; and determine the connected domains whose connected domain areas are greater than or equal to an area threshold as the candidate regions.

[0118] In one possible implementation, the generation module 503 is further used to: set the current position of the second image acquisition device as the initial position; set all candidate areas to an "unvisited" state; select a candidate area closest to the initial position from all "unvisited" candidate areas, and mark the nearest candidate area as "visited"; add the nearest candidate area to a path list; select a candidate area closest to the initial position from all "unvisited" candidate areas and repeat until all candidate areas are visited.

[0119] In one possible implementation, the generation module 503 is also used to: decompose the path list into a series of target points; generate a corresponding control instruction for each target point, the control instruction including a horizontal angle, a vertical angle, a moving speed, and a moving acceleration; calculate the time required from the current point to the next target point, and allocate an execution time for each of the control instructions; and sort each of the control instructions in sequence according to the path order to form a complete motion instruction.

[0120] In addition, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the device motion control method described in the above method embodiment are executed.

[0121] The computer program product of the device motion control method provided in the embodiment of the present application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the steps of the device motion control method described in the above method embodiment. Please refer to the above method embodiment for details, which will not be repeated here.

[0122] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0123] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0124] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk. It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variation thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus. In the absence of more restrictions, the elements defined by the sentence "includes..." do not exclude the presence of other identical elements in the process, method, article or apparatus that includes the elements.

[0125] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0126] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A device motion control method, characterized in that: include: Calculating a weight matrix of a historical event, wherein the historical event is a monitoring screen detection event on the first image acquisition device; Determine a candidate region according to the weight matrix; Generate a planned path based on the candidate area and generate corresponding motion instructions; The second image acquisition device is controlled by the motion instruction to perform a corresponding action, and the image acquisition range of the second image acquisition device is smaller than the image acquisition range of the first image acquisition device.

2. The method according to claim 1, characterized in that The calculation of the weight matrix of historical events includes: Calculate the weight growth function of each region; Calculate the weight distribution matrix of each historical event at the current time and the current latitude region according to the weight growth function; The weight matrix is ​​updated by the weight distribution matrix.

3. The method according to claim 2, characterized in that The updating of the weight matrix by using the weight distribution matrix comprises: For the area covered by the second image acquisition device in the previous round, the weight growth is set to 0; For the area not covered by the second image acquisition device in the previous round, the weight matrix is ​​updated according to the weight distribution matrix.

4. The method according to claim 1, characterized in that: The determining the candidate region according to the weight matrix comprises: Filtering the weight matrix by setting a threshold; Perform connected domain analysis on the filtered weight matrix; Classify the adjacent pixels that meet the conditions into the same connected domain, and obtain one or more connected domains; The candidate region is determined according to the connected domain.

5. The method according to claim 4, characterized in that The determining the candidate region according to the connected domain comprises: Calculating the connected domain area of ​​each of the connected domains; A connected domain whose area is greater than or equal to an area threshold is determined as the candidate region.

6. The method according to any one of claims 1 to 5, characterized in that: The generating a planned path based on the candidate area includes: Setting the current position of the second image acquisition device to an initial position; Set all candidate regions to "unvisited" status; Selecting a candidate region closest to the initial position from all "unvisited" candidate regions, and marking the closest candidate region as "visited"; Add the nearest candidate region to the path list; The candidate region closest to the initial position is selected from all “unvisited” candidate regions and the process is repeated until all candidate regions are visited.

7. The method according to claim 6, characterized in that The generating of corresponding motion instructions comprises: Decomposing the path list into a series of target points respectively; Generate a corresponding control instruction for each target point, wherein the control instruction includes a horizontal angle, a vertical angle, a moving speed, and a moving acceleration; Calculate the time required to reach the next target point from the current point, and assign execution time to each of the control instructions; According to the path sequence, each of the control instructions is sorted in sequence to form a complete motion instruction.

8. A device motion control device, characterized in that: include: A calculation module, used to calculate a weight matrix of a historical event, wherein the historical event is a monitoring screen detection event on the first image acquisition device; A determination module, used for determining a candidate region according to the weight matrix; A generation module, used to generate a planned path based on the candidate area and generate corresponding motion instructions; The control module is used to control the second image acquisition device to perform corresponding actions through the motion instruction.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of any method described in claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are executed.

Images