Target identification and positioning method and system based on linkage of multi-camera data acquisition equipment

Abstract

The invention relates to the technical field of recognition and positioning, in particular to a target recognition and positioning method and system based on linkage of multi-camera data acquisition equipment, and the method comprises the steps: sending a starting instruction to the multi-camera data acquisition equipment located in a classroom when a seating table obtaining instruction sent by a teacher terminal is received; when the multi-camera data acquisition equipment receives a starting instruction, a row seat picture and a column seat picture are shot; performing image recognition on the row seat picture, recognizing students belonging to the same row, and outputting a sorting identifier of the students; associating the student information with the sorting identifier based on an identification result of the image identification; based on the column seat pictures of the same row, seat occupation conditions are output, and the seat occupation conditions comprise non-occupation and determined occupation; sequentially matching the sorting identifiers of the students with column coordinates of a preset seating list, and filling the seating list with the student information; and feeding back the seating table to the teacher terminal. The seating table has the effect of preventing vacancy of the seating table.

Description

Technical Field

[0001] The present application relates to the field of identification and positioning technology, and in particular to a target identification and positioning method and system based on the linkage of multi-camera data acquisition equipment. Background Art

[0002] According to the patent entitled "An algorithm and system for constructing a student seating chart based on visual computing" (application number: CN118552755A), in a panoramic image, a preset plane coordinate system is first constructed, and the face areas in the detail images are matched to the plane coordinate system by comparing the image features of the detail images with the panoramic images, and the fitting coordinates of the face areas in each detail image are obtained. Then, the face areas belonging to the same row and column are identified through preset row and column integration rules. At the same time, each face area is pre-associated with student information, such as name, student number, etc.

[0003] However, when the student's position is offset or not in the direct line of sight of the camera, it is easy to fail to recognize the student, resulting in empty seats in the seating chart. Therefore, improvement is needed. Summary of the invention

[0004] In order to prevent empty seats from appearing in the seating chart, the present application provides a target recognition and positioning method and system based on the linkage of multi-camera data acquisition devices.

[0005] The first object of the invention of this application is achieved through the following technical solutions.

[0006] A target recognition and positioning method based on the linkage of multi-camera data acquisition equipment includes the following steps: When receiving a seating chart acquisition instruction from the teacher terminal, a start instruction is sent to the multi-camera data acquisition device located in the classroom; When the multi-camera data acquisition device receives the start command, it captures the row seat image and the column seat image; Perform image recognition on the row seat image, identify students belonging to the same row, and output the student ranking identifier; Based on the recognition result of the image recognition, the student information is associated with the sorting mark, and the student information includes name and student number; Outputting seat occupancy status based on the column seat picture of the same row, wherein the seat occupancy status includes unoccupied and confirmed occupied; Based on the seat occupancy, the student's sorting identifier is matched with the column coordinates of the preset seating chart in sequence, and the student information is filled into the seating chart; Feed the seating chart back to the teacher's terminal.

[0007] In a preferred embodiment, the step of performing image recognition on the row seat image, identifying students belonging to the same row, and outputting the students' ranking identifications comprises the steps of: Perform image processing on the row seat image to identify the student's head position; Map the identified student head positions to the preset panoramic image and output the student ranking identification.

[0008] In a preferred embodiment, the output of seat occupancy status based on the row seat picture of the same row, wherein the seat occupancy status includes the steps of unoccupied and occupied, comprises the steps of: Analyze the row seat images based on the image processing algorithm and output the status of each row seat image; When it is detected that the seat image is blurred and the student’s presence cannot be confirmed, the seat is marked as suspected to be occupied; Based on fuzzy rules, output seat occupancy status; When it is detected that the seat image is clear and the student is present, the seat is marked as definitely occupied.

[0009] In a preferred embodiment, the step of outputting seat occupancy status based on fuzzy rules comprises the steps of: Preprocess the row seat image and extract features from the preprocessed image; The features include the clarity of the head outline, the position of the head, the clarity of the outlines of other surrounding heads, the brightness of the picture, the shape of the head, and the outlines of other body parts; Functions that convert extracted features into fuzzy sets; In the function, the head outline clarity is expressed as low or high; When the head position is close to the center position, the head position is indicated as near; When the head position is not close to the center position, the head position is represented as far; The clarity of other head contours around is expressed as low or high; The picture brightness is expressed as low or high; When the head shape exists, it is indicated as yes; When the head shape does not exist, it is indicated as no; The other body part contours are represented as low and high.

[0010] In a preferred embodiment, the step of outputting seat occupancy status based on fuzzy rules further includes the steps of: When the input head outline clarity is indicated as high and the head position is indicated as close, the seat is marked as definitely occupied; When the input head outline clarity is indicated as low, the head shape is indicated as yes, and the surrounding other head outline clarity is indicated as low, then the seat is marked as definitely occupied; When the input head contour clarity is indicated as low and the contour clarity of other body parts is indicated as high, the seat is marked as definitely occupied.

[0011] In a preferred embodiment, the step of matching the student's sorting identifier with the column coordinates of the preset seating chart in sequence based on the seat occupancy status and filling the student information into the seating chart comprises the steps of: The preset seating chart includes the column coordinates and row numbers of all seats; Based on the recognition result of image recognition, output the row number that needs to be matched currently; From the preset seating chart, extract all column coordinates of the row number to form a list.

[0012] In a preferred embodiment, the step of matching the student's sorting identifier with the column coordinates of the preset seating chart in sequence based on the seat occupancy status and filling the student information into the seating chart further includes the steps of: SA1: Determine whether the sorting identifiers of students belonging to the same row match the list; SA2: When occupancy is confirmed, match and fill in the student's name in the seating chart; SA3: When it is not occupied, it is not matched, and SA1-SA2 are executed for the next seat in sequence until all students' names are filled in.

[0013] The second object of the invention of this application is achieved through the following technical solutions: A target recognition and positioning system based on the linkage of multi-camera data acquisition equipment, comprising: Receiving module: When receiving the seating chart acquisition instruction from the teacher terminal, it sends a start instruction to the multi-camera data acquisition device in the classroom; Start the shooting module: when the multi-camera data acquisition device receives the start command, it shoots the row seat picture and the column seat picture; Identification and sorting module: Perform image recognition on the row seat image, identify students belonging to the same row, and output the student sorting identifier; Information acquisition module: Based on the recognition results of image recognition, the student information is associated with the sorting mark. The student information includes name and student number; Output module: output seat occupancy status based on the column seat picture of the same row, the seat occupancy status includes unoccupied and confirmed occupied; Matching module: Based on the seat occupancy, the student's sorting identifier is matched with the column coordinates of the preset seating chart in sequence, and the student information is filled into the seating chart; Feedback module: Feedback the seating chart to the teacher terminal.

[0014] The third object of the invention is achieved by the following technical solutions: A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the target recognition and positioning method based on the linkage of multi-camera data acquisition devices are implemented.

[0015] The fourth object of the invention of this application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned target recognition and positioning method based on the linkage of multi-camera data acquisition devices.

[0016] In summary, the present application includes at least one of the following beneficial technical effects: The teacher sends a command through his terminal device (such as a laptop, tablet, etc.) to ask the system to generate a seating chart. After receiving this command, the system sends a start signal to multiple data acquisition devices (such as cameras) in the classroom to instruct them to start working. After receiving the start command, each data acquisition device starts to perform their tasks. They will take pictures of the seats in the classroom from different angles to ensure that all seats are covered. These devices will take pictures of the row seats (i.e., the horizontal seats) and the column seats (i.e., the vertical seats) for subsequent image processing and recognition. The system uses image recognition technology to analyze the row seats to identify students sitting in the same row. The system assigns a sorting identifier to each identified student, which indicates the horizontal position of the student relative to the classroom and corresponds the student to a specific seat. The system uses the image recognition results identified in the previous step to associate the student information with the sorting identifier. This information usually includes the student's name and student number, which are pre-associated with the student's image or other identification information. The system analyzes the column seats to determine whether each seat is occupied, which seats have students, and which seats are empty. Once the system determines that a seat is occupied, it matches the ranking ID of the student occupying that seat with the column coordinates in the preset seating chart. This allows the system to fill in the student's name to the correct seat, thus completing the seating chart. The generated seating chart is sent back to the teacher's terminal device. The teacher can then view and confirm the seating chart to understand the student's seat assignment and may make further adjustments or confirmations. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flowchart of an implementation of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices in the present application; Figure 2This is a flowchart of implementing step S30 in an embodiment of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices of the present application; Figure 3 This is a flowchart of implementing step S50 in an embodiment of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices of the present application; Figure 4 This is a flowchart for implementing step S503 in an embodiment of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices of the present application; Figure 5 This is another implementation flow chart of step S503 in an embodiment of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices of the present application; Figure 6 This is a flowchart of implementing step S60 in an embodiment of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices of the present application; Figure 7 This is another implementation flow chart of step S60 in an embodiment of a method for target recognition and positioning based on linkage of multi-camera data acquisition devices of the present application; Figure 8 This is a principle block diagram of a computer device of the present application. DETAILED DESCRIPTION

[0018] The following is combined with Figure 1-8 This application is described in further detail.

[0019] In one embodiment, if Figure 1 As shown, the present application discloses a target recognition and positioning method based on the linkage of multi-camera data acquisition devices, which specifically includes the following steps: S10: When receiving a seating chart acquisition instruction from the teacher terminal, sending a start instruction to a multi-camera data acquisition device in the classroom; In this embodiment, the process of receiving and processing instructions is involved. Specifically, the teacher sends an instruction through his terminal device (such as a laptop, tablet computer, etc.) to ask the system to generate a seating chart. After receiving this instruction, the system sends a start signal to multiple data acquisition devices (such as cameras) in the classroom to instruct them to start working.

[0020] S20: When the multi-camera data acquisition device receives the start command, it captures the row seat image and the column seat image; In this embodiment, after receiving the start command, each data acquisition device starts to perform its tasks. They will take pictures of the seats in the classroom from different angles to ensure that all seats are covered. These devices will take pictures of row seats (i.e., horizontal seats) and column seats (i.e., vertical seats) to facilitate subsequent image processing and recognition.

[0021] S30: Perform image recognition on the row seat image, identify students belonging to the same row, and output the student ranking identifiers; In this embodiment, the system uses image recognition technology to analyze the row seat image to identify students sitting in the same row. The system assigns a sorting mark to each identified student, which indicates the horizontal position of the student relative to the classroom, and corresponds the student to a specific seat.

[0022] S40: Based on the recognition result of the image recognition, the student information is associated with the sorting identifier, where the student information includes name and student number; In this embodiment, the system uses the image recognition results identified in the previous step to associate the student information with the sorting mark. This information usually includes the student's name and student number, which are pre-associated with the student's image or other identification information.

[0023] S50: Based on the column seat picture of the same row, output seat occupancy status, wherein the seat occupancy status includes unoccupied and confirmed occupied; In this embodiment, the system analyzes the seating column view to determine whether each seat is occupied, which seats have students, and which seats are empty.

[0024] S60: Based on the seat occupancy situation, the student's sorting identifier is matched with the column coordinates of the preset seating table in sequence, and the student information is filled into the seating table; In this embodiment, when the system determines that a seat is occupied, it will match the ranking identifier of the student occupying the seat with the column coordinates in the preset seating chart. In this way, the system can fill in the student's name on the correct seat, thereby completing the seating chart.

[0025] S70: Feedback the seating chart to the teacher terminal.

[0026] In this embodiment, the generated seating chart is sent back to the teacher's terminal device, so that the teacher can view and confirm the seating chart, understand the seat allocation of the students, and possibly make further adjustments or confirmations.

[0027] Figure 2 , step S30, comprising the steps of: S301: Perform image processing on the row seat image to identify the head position of the student; S302: Map the identified student head positions to a preset panoramic image and output the student's sorting identifier.

[0028] In this embodiment, the detailed operation flow of steps S301 to S302 is as follows: Step S301 uses image processing technology to analyze the row seat image captured by the camera, and identifies and marks the head position of each student through an algorithm, which may include face detection or head contour recognition. In step S302, the system converts and maps the head position information into a pre-set panoramic image system to determine the specific column position of each student in the classroom and output the corresponding sorting mark.

[0029] Figure 3 , step S50, comprising the steps of: S501: Analyze the row seat picture based on the image processing algorithm and output the status of each row seat picture; S502: When it is detected that the seat image is blurred and the presence of the student cannot be determined, the seat is marked as suspected to be occupied; S503: Output seat occupancy status based on fuzzy rules; S504: When it is detected that the seat image is clear and the student is present, the seat is marked as definitely occupied.

[0030] In this embodiment, the detailed explanation of steps S501 to S504 is as follows: Step S501 involves using an image processing algorithm to analyze the image of each row of seats to determine the status of the seat, which includes contrast enhancement, edge detection and other technologies to determine whether there are students in the image. Then, in step S502, if the algorithm detects that the seat image becomes blurred due to movement or other reasons, and it is not possible to clearly determine whether there are students sitting in the seat, the system will mark the seat as "suspected occupation", indicating that there is uncertainty. In step S503, the system applies fuzzy rules to handle these uncertain situations and outputs a probability-based seat occupancy status. These rules help the system make the best estimate when the information is incomplete. Finally, in step S504, if the algorithm determines that the seat image is clear and clearly detects the presence of a student, the system will mark the seat as "confirmed occupation", which means that the seat is indeed used by a student. This series of steps ensures accurate judgment of the seat occupancy status and provides teachers with real-time classroom management information.

[0031] Figure 4 , step S503, comprising the steps of: SB1: preprocess the row seat image and extract features from the preprocessed image; SB2: The features include head outline clarity, head position, other head outline clarity around, picture brightness, head shape, and other body part outlines; SB3: Function that converts the extracted features into fuzzy sets; SB4: In the function, the head outline clarity is expressed as low or high; SB5: When the head position is close to the center position, the head position is represented as near; SB6: When the head position is not close to the center position, the head position is represented as far; SB7: The clarity of other head contours around is expressed as low or high; SB8: The picture brightness is expressed as low or high; SB9: When the head shape exists, it indicates yes; SB10: when the head shape does not exist, it indicates no; SB11: The contours of the other body parts are expressed as low and high.

[0032] In this embodiment, steps SB1 to SB11 involve feature extraction and fuzzification of the row seat image, which is explained in detail below: SB1 first pre-processes the row seat image captured by the camera, such as denoising, contrast enhancement, etc., so that the features in the image can be more clearly identified. Then, the system extracts key features from the processed image, which will be used for subsequent fuzzy logic analysis. SB2: The system identifies and extracts a series of features that help determine whether the seat is occupied. These features include but are not limited to the clarity of the head outline, the position of the head in the picture, the clarity of other heads around, the brightness of the entire picture, the presence or absence of the head shape, and the outlines of other body parts (such as shoulders, arms). SB3: The system converts these extracted features into fuzzy sets in fuzzy logic. Fuzzy sets allow the system to deal with uncertainty and ambiguity, because many situations in the real world are not black and white. SB4 to SB10: These steps define how to map each feature to a fuzzy set. For example, the clarity of the head outline can be expressed as "low" or "high", the head position can be expressed as "near" (close to the center position) or "far" (not close to the center position), and the clarity of other head outlines and the brightness of the picture can also be expressed as "low" or "high". The existence of the head shape can be expressed as "yes" or "no". SB11: Finally, this step converts the clarity of the outlines of other body parts into fuzzy sets, which can be "low" or "high", which helps to further confirm whether there are students in the seats. Through these steps, the system can use fuzzy logic to process and analyze image features to more accurately determine the seat occupancy status.

[0033] Figure 5 , step S503 further includes the steps of: SC1: When the input head outline clarity is indicated as high and the head position is indicated as close, the seat is marked as definitely occupied; SC2: When the input head contour clarity is indicated as low, the head shape is indicated as yes, and the surrounding other head contour clarity is indicated as low, then mark the seat as definitely occupied; SC3: When the input head contour clarity is indicated as low and the contour clarity of other body parts is indicated as high, the seat is marked as definitely occupied.

[0034] In this embodiment, steps SC1 to SC3 are based on fuzzy logic rules to determine whether a seat is occupied. The following is a detailed explanation: SC1: This rule indicates that if the system determines through image processing analysis that the head outline on a certain seat is very clear (i.e., "high") and the head is located in the central area of ​​the picture (i.e., "near"), then the system is confident enough to believe that there is a student in the seat, so it is marked as "definitely occupied". This situation usually means that the image quality is good and the position of the student's head is clear, allowing the system to make a direct judgment. SC2: This rule applies to situations where the image quality is poor or the head is partially blocked. Even if the clarity of the head outline is not high (i.e., "low"), if the system can still recognize the head shape (i.e., "yes") and there are no other obvious head outlines around (i.e., the clarity of the surrounding head outlines is "low"), the system will also believe that there is a student in the seat and mark it as "definitely occupied". This shows that the system can still make reasonable judgments when processing fuzzy or incomplete information. SC3: This rule takes into account the situation when the head outline is not clear, but the outlines of other body parts (such as shoulders and arms) are clearly visible. If the head outline is low (i.e. "low"), but other body parts are detected with high outline clarity (i.e. "high"), the system infers that there is a student in that seat and marks it as "definitely occupied". This helps the system determine the seat occupancy status through clues from other body parts when the head is not fully visible. These steps improve the accuracy and reliability of the system in determining the seat occupancy status in complex environments through fuzzy logic rules and combining different image features.

[0035] Figure 6 , step S60, comprising the steps of: S601: The preset seating table includes the column coordinates and row numbers of all seats; S602: Based on the recognition result of the image recognition, output the row number that currently needs to be matched; S603: Extract all column coordinates of the row number from the preset seating chart to form a list.

[0036] In this embodiment, first, the system will have a pre-set seating chart, which is a detailed record of the specific location of each seat in the classroom. Each seat is uniquely identified by a column coordinate (such as A, B, C, etc.) and a row number (such as 1, 2, 3, etc.), so that the specific location of each seat in the classroom can be accurately pointed out. When the system receives the seating chart acquisition instruction issued by the teacher terminal and starts the multi-camera data acquisition device, these devices will take pictures of the seats in the classroom. By performing image recognition processing on these pictures, the system can determine the position of the students in the picture and identify the row number where the students are located. This row number is the key information for the system to match the seats next. Once the row number to be matched is determined, the system will refer to the preset seating chart and extract all the seat column coordinates of the corresponding row number. These column coordinates form a list according to the order of the seats (from left to right or from right to left). This list is the benchmark used by the system to match with the student sorting identifier, ensuring that the information of each student can be accurately filled in the corresponding position of the seating chart. In this way, the system can ensure that the information of the seating chart matches the seat occupancy in the actual classroom.

[0037] Figure 7 , step S60 further includes the steps of: SA1: Determine whether the sorting identifiers of students belonging to the same row match the list; SA2: When occupancy is confirmed, match and fill in the student's name in the seating chart; SA3: When it is not occupied, it is not matched, and SA1-SA2 are executed for the next seat in sequence until all students' names are filled in.

[0038] In this embodiment, steps SA1 to SA3 involve matching the actual seats of students with the preset seating chart and updating the seating chart information accordingly, as explained in detail below: SA1: This step first requires identifying the actual seat positions of students in the same row. The system obtains the student's seat column coordinates (i.e., the student's lateral position in the classroom) and compares them with the column coordinates in the preset seating chart. The purpose of this step is to determine whether the students are sitting where they should be. SA2: If the system confirms that there is a student in a certain seat (through the previous image processing and analysis steps) and the column coordinates of the seat match the column coordinates in the preset seating chart, the system will fill in the student's name in the corresponding position of the seating chart. This indicates that the student is sitting in the correct position and the seating chart is updated accordingly. SA3: If the system finds that there is no student in a certain seat, or the student's actual seat column coordinates do not match the column coordinates of the preset seating chart, the system will not fill in the name in the seating chart position. Instead, the system will continue to check the next seat and repeat steps SA1 and SA2 until all students' names are correctly filled in the seating chart. This process ensures that the seating chart reflects the actual situation as much as possible even if there are students absent or sitting in the wrong position. Together, these steps form an automated process for updating the seating chart based on students' actual seating, providing teachers with accurate student attendance and seating assignment information.

[0039] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0040] In one embodiment, a target recognition and positioning system based on the linkage of multiple camera data acquisition devices is provided, and the target recognition and positioning system based on the linkage of multiple camera data acquisition devices corresponds to the target recognition and positioning method based on the linkage of multiple camera data acquisition devices in the above embodiment. The target recognition and positioning system based on the linkage of multiple camera data acquisition devices includes: Receiving module: When receiving the seating chart acquisition instruction from the teacher terminal, it sends a start instruction to the multi-camera data acquisition device in the classroom; Start the shooting module: when the multi-camera data acquisition device receives the start command, it shoots the row seat picture and the column seat picture; Identification and sorting module: Perform image recognition on the row seat image, identify students belonging to the same row, and output the student sorting identifier; Information acquisition module: Based on the recognition results of image recognition, the student information is associated with the sorting mark. The student information includes name and student number; Output module: output seat occupancy status based on the column seat picture of the same row, the seat occupancy status includes unoccupied and confirmed occupied; Matching module: Based on the seat occupancy, the student's sorting identifier is matched with the column coordinates of the preset seating chart in sequence, and the student information is filled into the seating chart; Feedback module: Feedback the seating chart to the teacher terminal.

[0041] Optionally, also include: Image processing module: perform image processing on the row seat image to identify the head position of the student; Mapping module: maps the identified student head positions to the preset panoramic image and outputs the student's sorting identification.

[0042] Optionally, also include: Output status module: Analyze the row seat picture based on the image processing algorithm and output the status of each row seat picture; The first detection module: when it is detected that the seat image is blurred and the student cannot be confirmed to be present, the seat is marked as suspected to be occupied; Fuzzy rule module: output seat occupancy status based on fuzzy rules; The second detection module: When it is detected that the seat image is clear and the student is present, the seat is marked as occupied.

[0043] Optionally, also include: Preprocessing module: preprocess the row seat image and extract features from the preprocessed image; Feature module: The features include head outline clarity, head position, other head outline clarity around, picture brightness, head shape, and other body part outlines; Conversion module: a function that converts the extracted features into fuzzy sets; First representation module: In the function, the head outline clarity is represented as low or high; The second representation module: when the head position is close to the center position, the head position is represented as near; The third representation module: when the head position is not close to the center position, the head position is represented as far; The fourth representation module: the clarity of the contours of other surrounding heads is represented as low or high; The fifth representation module: the picture brightness is represented as low or high; The sixth representation module: when the head shape exists, it is represented as yes; The seventh representation module: when the head shape does not exist, it is represented as no; The eighth representation module: the contours of other body parts are represented as low and high.

[0044] Optionally, also include: The first fuzzy rule module: when the input head outline clarity is expressed as high and the head position is expressed as close, the seat is marked as definitely occupied; When the second fuzzy rule module: the input head contour clarity is expressed as low, the head shape is expressed as yes, and the surrounding other head contour clarity is expressed as low, then mark the seat as confirmed occupied; The third fuzzy rule module: when the input head contour clarity is expressed as low and the contour clarity of other body parts is expressed as high, the seat is marked as definitely occupied.

[0045] Optionally, also include: Preset seating chart module: The preset seating chart includes the column coordinates and row numbers of all seats; Output line number module: Based on the recognition results of image recognition, output the line number that currently needs to be matched; Extract list module: extract all column coordinates of the row number from the preset seating chart to form a list.

[0046] Optionally, also include: Judgment module: SA1: Determine whether the sorting identifiers of students belonging to the same row match the list; First matching module: SA2: When occupancy is confirmed, match and fill in the student name in the seating chart; Second matching module: SA3: When it is not occupied, it is not matched, and SA1-SA2 are executed for the next seat in sequence until all students' names are filled in.

[0047] For the specific definition of a target recognition and positioning system based on the linkage of multi-camera data acquisition devices, please refer to the definition of a target recognition and positioning method based on the linkage of multi-camera data acquisition devices mentioned above, which will not be repeated here. Each module in the above-mentioned target recognition and positioning system based on the linkage of multi-camera data acquisition devices can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0048] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store a seating chart. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a target recognition and positioning method based on the linkage of multi-camera data acquisition devices is implemented.

[0049] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a target recognition and positioning method based on the linkage of multiple-camera data acquisition devices is implemented.

[0050] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a method for target recognition and positioning based on the linkage of multi-camera data acquisition devices is provided.

[0051] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0052] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A target recognition and positioning method based on the linkage of multi-camera data acquisition equipment, characterized in that: Includes steps: When receiving a seating chart acquisition instruction from the teacher terminal, a start instruction is sent to the multi-camera data acquisition device located in the classroom; When the multi-camera data acquisition device receives the start command, it captures the row seat image and the column seat image; Perform image recognition on the row seat image, identify students belonging to the same row, and output the student ranking identifier; Based on the recognition result of the image recognition, the student information is associated with the sorting mark, and the student information includes name and student number; Outputting seat occupancy status based on the column seat picture of the same row, wherein the seat occupancy status includes unoccupied and confirmed occupied; Based on the seat occupancy, the student's sorting identifier is matched with the column coordinates of the preset seating chart in sequence, and the student information is filled into the seating chart; Feed the seating chart back to the teacher's terminal.

2. The target recognition and positioning method based on the linkage of multiple camera data acquisition devices according to claim 1 is characterized in that: The step of performing image recognition on the row seat screen, identifying students belonging to the same row, and outputting the students' sorting identifiers comprises the following steps: Perform image processing on the row seat image to identify the student's head position; Map the identified student head positions to the preset panoramic image and output the student ranking identification.

3. The target recognition and positioning method based on the linkage of multiple camera data acquisition devices according to claim 1 is characterized in that: The step of outputting seat occupancy status based on the row seat picture of the same row, wherein the seat occupancy status includes the steps of being unoccupied and being determined to be occupied, comprises the steps of: Analyze the row seat images based on the image processing algorithm and output the status of each row seat image; When it is detected that the seat image is blurred and the student’s presence cannot be confirmed, the seat is marked as suspected to be occupied; Based on fuzzy rules, output seat occupancy status; When it is detected that the seat image is clear and the student is present, the seat is marked as definitely occupied.

4. The target recognition and positioning method based on the linkage of multiple camera data acquisition devices according to claim 3 is characterized in that: The step of outputting seat occupancy status based on fuzzy rules comprises the steps of: Preprocess the row seat image and extract features from the preprocessed image; The features include the clarity of the head outline, the position of the head, the clarity of the outlines of other surrounding heads, the brightness of the picture, the shape of the head, and the outlines of other body parts; Functions that convert extracted features into fuzzy sets; In the function, the head outline clarity is expressed as low or high; When the head position is close to the center position, the head position is indicated as near; When the head position is not close to the center position, the head position is represented as far; The clarity of other head contours around is expressed as low or high; The picture brightness is expressed as low or high; When the head shape exists, it is indicated as yes; When the head shape does not exist, it is represented as no; The other body part contours are represented as low and high.

5. The target recognition and positioning method based on the linkage of multiple camera data acquisition devices according to claim 3 is characterized in that: The step of outputting seat occupancy status based on fuzzy rules also includes the steps of: When the input head outline clarity is indicated as high and the head position is indicated as close, the seat is marked as definitely occupied; When the input head outline clarity is indicated as low, the head shape is indicated as yes, and the clarity of other surrounding head outlines is indicated as low, then the seat is marked as definitely occupied; When the input head contour clarity is indicated as low and the contour clarity of other body parts is indicated as high, the seat is marked as definitely occupied.

6. The target recognition and positioning method based on the linkage of multiple camera data acquisition devices according to claim 1 is characterized in that: The step of matching the student's sorting identifier with the column coordinates of the preset seating table in sequence based on the seat occupancy situation and filling the student information into the seating table comprises the steps of: The preset seating chart includes the column coordinates and row numbers of all seats; Based on the recognition result of image recognition, output the row number that needs to be matched currently; From the preset seating chart, extract all column coordinates of the row number to form a list.

7. The target recognition and positioning method based on the linkage of multiple camera data acquisition devices according to claim 1 is characterized in that: The step of matching the student's sorting identifier with the column coordinates of the preset seating table in sequence based on the seat occupancy situation and filling the student information into the seating table further includes the steps of: SA1: Determine whether the sorting identifiers of students belonging to the same row match the list; SA2: When occupancy is confirmed, match and fill in the student's name in the seating chart; SA3: When it is not occupied, it is not matched, and SA1-SA2 are executed for the next seat in sequence until all students' names are filled in.

8. A target recognition and positioning system based on the linkage of multi-camera data acquisition equipment, characterized in that: include: Receiving module: When receiving the seating chart acquisition instruction from the teacher terminal, it sends a start instruction to the multi-camera data acquisition device in the classroom; Start the shooting module: when the multi-camera data acquisition device receives the start command, it shoots the row seat picture and the column seat picture; Identification and sorting module: Perform image recognition on the row seat image, identify students belonging to the same row, and output the student sorting identifier; Information acquisition module: Based on the recognition results of image recognition, the student information is associated with the sorting mark. The student information includes name and student number; Output module: output seat occupancy status based on the column seat picture of the same row, the seat occupancy status includes unoccupied and confirmed occupied; Matching module: Based on the seat occupancy, the student's sorting identifier is matched with the column coordinates of the preset seating chart in sequence, and the student information is filled into the seating chart; Feedback module: Feedback the seating chart to the teacher terminal.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of a target recognition and positioning method based on the linkage of multi-camera data acquisition devices as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps of a target recognition and positioning method based on the linkage of multi-camera data acquisition devices as described in any one of claims 1 to 7 are implemented.

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