Method and device for identifying number of people in amusement equipment, computer equipment and storage medium

Abstract

The invention relates to an amusement equipment people number identification method and device, computer equipment and a storage medium. The amusement equipment people number identification method comprises the following steps: acquiring a to-be-processed video corresponding to target equipment and the operation time of the target equipment; performing framing processing on the to-be-processed video based on a preset algorithm and the operation time of the target equipment to obtain an image frame set; and performing human body feature recognition on the image frame set, determining the number of people on the target equipment, and sending the number of people to a background. According to the method, the video data of the amusement equipment is acquired, framing processing is performed in combination with the operation time of the amusement equipment, then human body feature recognition is performed on the image frames to obtain the number of tourists on the amusement equipment, and the number of tourists is sent to the background, so that statistics of the amount of tourists received by the amusement equipment is realized; and an amusement park operator can make a corresponding operation strategy and adjust the maintenance frequency of amusement equipment according to the number of received tourists.

Description

Technical Field

[0001] The present invention relates to the technical field of amusement equipment, and in particular to a method, a device, a equipment and a storage medium for identifying the number of people in an amusement equipment. Background Art

[0002] With the rapid development of the national economy and the continuous improvement of people's living standards, people's demand for amusement park activities has become increasingly strong. Amusement equipment is a mechanical facility for tourists to play. At present, the method commonly used in amusement parks is to count the number of tourists manually by staff. This method is not only inefficient, but also prone to errors, especially during peak hours when a large number of tourists flock to a certain amusement equipment. Manual counting can hardly achieve accurate statistics. In addition, manual counting cannot provide real-time data, making it difficult for managers to understand the operating status of the equipment in a timely manner, affecting the scientificity and timeliness of amusement park operation decisions. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method, device, equipment and storage medium for identifying the number of people in an amusement device.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0005] The present invention is achieved through the following technical solutions:

[0006] In a first aspect, this embodiment provides a method for identifying the number of people in an amusement device, comprising the following steps:

[0007] Obtain the to-be-processed video corresponding to the target device and the target device running time;

[0008] Processing the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set;

[0009] Human body feature recognition is performed on the image frame set to determine the number of people on the target device, and the number of people is sent to the background.

[0010] Furthermore, the step of processing the video to be processed by framing to obtain an image frame set based on a preset algorithm and the target device running time includes:

[0011] Obtaining a video reference time of the video to be processed;

[0012] Extracting a target video from the video to be processed based on the video reference time and the target device running time;

[0013] The target video is frame-processed based on the preset algorithm to obtain an image frame set.

[0014] Furthermore, the step of performing frame processing on the target video based on the preset algorithm to obtain an image frame set includes:

[0015] Splitting the target video into multiple sub-videos based on the preset algorithm;

[0016] Segmenting the plurality of sub-videos based on a preset frame interval to obtain sliced ​​videos;

[0017] Feature extraction is performed on each of the segmented videos to obtain an image frame set.

[0018] Furthermore, the step of extracting features from each of the sliced ​​videos to obtain an image frame set includes:

[0019] Decomposing each of the segmented videos to obtain a set of video frames;

[0020] A target frame image is selected from the video frame set, and features are extracted from the target frame image and adjacent frame images to obtain an image frame set.

[0021] Furthermore, the step of performing human feature recognition on the image frame set to determine the number of people on the target device includes:

[0022] Extracting boundary features of each frame of the image in the image frame set to determine a boundary box corresponding to each frame of the image;

[0023] Determine the number of human features in each frame of the image based on the bounding box;

[0024] The number of people on the target device is determined based on the number of human body features.

[0025] Furthermore, the step of extracting boundary features from each frame of the image in the image frame set and determining a boundary box corresponding to each frame of the image includes:

[0026] Determine the target area of ​​each frame of the image, and mark the target area with a target angle;

[0027] The marked target area is processed based on a neural network to obtain the bounding box.

[0028] Furthermore, the step of determining the number of human features in each frame of image based on the boundary data includes:

[0029] Performing first target recognition on each frame of the image based on the bounding box and the YOLOV5 algorithm to obtain a first target sample;

[0030] Performing second target recognition on each frame of the picture based on the bounding box and the CrowdCounting algorithm to obtain a second target sample;

[0031] The number of human body features is determined according to the first target sample and the second target sample.

[0032] In a second aspect, the present embodiment provides a device for identifying the number of people in an amusement device, including: an acquisition unit, a processing unit, and an identification unit;

[0033] The acquisition unit is used to acquire the to-be-processed video corresponding to the target device and the target device running time;

[0034] The processing unit is used to process the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set;

[0035] The recognition unit is used to perform human feature recognition on the image frame set, determine the number of people on the target device, and send the number of people to the background.

[0036] In a third aspect, this embodiment provides a computer device, which includes a memory and a processor, wherein a computer program is stored on the processor, and when the processor executes the computer program, the method for identifying the number of people in an amusement device as described in any one of claims 1-7 is implemented.

[0037] In a fourth aspect, this embodiment provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the method for identifying the number of people in an amusement device as described in any one of claims 1-7 can be implemented.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows: by acquiring the video data of the amusement equipment and performing frame processing in combination with the running time of the amusement equipment, human feature recognition is then performed on the image frame to obtain the number of people on the amusement equipment, and the number is sent to the background, so as to realize the statistics of the number of tourists received by the amusement equipment, so that the operator of the amusement park can make corresponding business strategies and adjust the maintenance frequency of the amusement equipment according to the number of tourists received. At the same time, the amusement park manager can optimize the layout and opening hours of the amusement equipment.

[0039] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following preferred embodiments are specifically cited and described in detail as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a flow chart of a method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0041] Figure 2 A schematic diagram of a flow chart of executing step S2 in the method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of a flow chart of executing step S23 in the method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of a flow chart of executing step S233 in the method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0044] Figure 5 A schematic diagram of a flow chart of executing step S3 in the method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0045] Figure 6 A schematic diagram of a flow chart of executing step S31 in the method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0046] Figure 7 A schematic diagram of a flow chart of executing step S32 in the method for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0047] Figure 8 A schematic block diagram of a device for identifying the number of people in an amusement device provided by an embodiment of the present invention;

[0048] Fig. 9 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0051] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0052] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0053] See also Figure 1 In the specific embodiment shown, the present invention discloses a method for identifying the number of people in a manned amusement device, comprising the following steps:

[0054] Step S1, obtaining the to-be-processed video corresponding to the target device and the target device running time;

[0055] It is understandable that the high-definition camera on the amusement equipment can capture the complete view of the equipment and its surroundings. The time point of video acquisition is combined with the operation time of the amusement equipment to ensure that the recorded video can reflect the flow of people during the use of the equipment. In this example, after obtaining the video to be processed corresponding to the target device, it will be pre-processed to ensure that the video quality can be used for human feature recognition. Preprocessing includes denoising, color correction, etc. to improve the accuracy of human feature recognition.

[0056] Step S2, processing the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set;

[0057] It is understandable that the preset algorithm is used to divide the video stream into multiple image frame sets according to the running time of the amusement equipment. Each frame set corresponds to a complete equipment operation cycle, ensuring that the timestamp of each image frame set is consistent with the running time of the equipment to avoid statistical errors caused by time errors. According to the preset video frame rate, ensure that each image frame set contains enough frames for accurate human feature recognition. And perform denoising, enhancement and other processing on each image frame to improve the image quality and ensure the accuracy of human feature recognition.

[0058] Through the above steps, the video to be processed is converted into an image frame set suitable for human feature recognition. At the same time, the timestamp of the image frame set is consistent with the running time of the device, avoiding statistical errors caused by time errors and improving the reliability of the data.

[0059] Step S3, performing human feature recognition on the image frame set, determining the number of people on the target device, and sending the number of people to the background.

[0060] It can be understood that a pre-trained deep learning model (such as a convolutional neural network) is used to perform human body detection on each image frame, identify key information such as pedestrian outlines and head positions in the image, and analyze individual position changes in multiple consecutive frames to avoid repeated counting and ensure the accuracy of head counting. Based on the detected human features and individual tracking results, the actual number of people in each image frame set is calculated.

[0061] Through the above steps, human features are recognized based on the image frame set and the number of people on the amusement equipment is determined, which provides data support for the management and operation of the amusement equipment and improves the operational efficiency and safety of the amusement equipment.

[0062] Through steps S1 to S3, the number of tourists received by the amusement equipment is counted, so that the operator of the amusement park can make corresponding business strategies and adjust the maintenance frequency of the amusement equipment according to the number of tourists received. At the same time, the amusement park manager can optimize the layout and opening hours of the amusement equipment.

[0063] See also Figure 2 The step of processing the video to be processed by framing to obtain an image frame set based on a preset algorithm and the target device running time includes:

[0064] S21, obtaining the video reference time of the video to be processed;

[0065] It is understandable that the video base time is: min(T 11 ∪T 12 ∪...∪T ij )......(i is the session number, j is the equipment number), Tij represents the time range in which the jth cabin of the i-th session obtains all tourists.

[0066] S22, extracting a target video from the video to be processed based on the video reference time and the target device running time;

[0067] S23, performing frame processing on the target video based on the preset algorithm to obtain an image frame set.

[0068] Through steps S21 to S23, it is ensured that the timestamp of the target video is consistent with the operating time of the device, thereby avoiding statistical errors caused by time errors, extracting video clips within the video reference time, so that each image frame set only contains one complete device operation cycle, and the extracted target video clips are frame-processed at a preset frame rate to generate an image frame set to improve data accuracy.

[0069] In one embodiment, see Figure 3 The step of performing frame processing on the target video based on the preset algorithm to obtain an image frame set includes:

[0070] S231, dividing the target video into a plurality of sub-videos based on the preset algorithm;

[0071] S232, dividing the plurality of sub-videos based on a preset frame interval to obtain segmented videos;

[0072] S233, extracting features from each of the segmented videos to obtain an image frame set.

[0073] Through steps S231 to S233, it is ensured that the timestamp of each sub-video is consistent with the running time of the device to avoid statistical errors caused by time errors, and each sub-video is further divided into multiple sliced ​​videos according to a preset frame interval (such as extracting one frame per second) to ensure that each sliced ​​video contains enough frames for accurate human feature recognition. Feature extraction is performed on each sliced ​​video to improve the quality of the image frame set.

[0074] In one embodiment, see Figure 4 The step of extracting features from each of the sliced ​​videos to obtain an image frame set comprises:

[0075] S2331, disassemble each of the segmented videos to obtain a set of video frames;

[0076] S2332, selecting a target frame image from the video frame set, and performing feature extraction on the target frame image and adjacent frame images to obtain an image frame set.

[0077] Through steps S2331 to S2332, a frame with a large motion change is selected as the target frame to ensure that the detected pedestrian is real and reduce false detection and missed detection. The previous frame and the next frame of the target frame are selected as adjacent frame images, which can better capture the motion trajectory of the pedestrian and improve the accuracy of feature extraction.

[0078] In one embodiment, see Figure 5 The step of performing human feature recognition on the image frame set to determine the number of people on the target device includes:

[0079] S31, extracting boundary features of each frame of the image in the image frame set, and determining a boundary box corresponding to each frame of the image;

[0080] S32, determining the number of human features in each frame of image based on the bounding box;

[0081] S33: Determine the number of people on the target device based on the number of human body features.

[0082] Through steps S31 to S33, target detection is performed on each frame of image, and the human body boundary box in the image is determined. Human body features are extracted from each boundary box to ensure that each detected human body is correctly counted to avoid missing detection and false detection.

[0083] In one embodiment, see Figure 6 The step of extracting boundary features from each frame of the image in the image frame set and determining a boundary box corresponding to each frame of the image comprises:

[0084] S311, determining a target area of ​​each frame of image, and marking a target angle of the target area;

[0085] S312: Process the labeled target area based on a neural network to obtain the bounding box.

[0086] Through steps S311 to S312, the target area in each frame of the image is determined, background interference is reduced, the accuracy of human body detection is improved, and the target angle of the target area is marked, which helps to improve the neural network's ability to recognize human body posture, reduce false detection and missed detection, and extract human body features from each bounding box to ensure that the human body features of each frame of the image are counted.

[0087] In one embodiment, see Figure 7 The step of determining the number of human features in each frame image based on the boundary data comprises:

[0088] S321, performing first target recognition on each frame of the image based on the bounding box and the YOLOV5 algorithm to obtain a first target sample;

[0089] S322, performing second target recognition on each frame of the image based on the bounding box and the CrowdCounting algorithm to obtain a second target sample;

[0090] S323: Determine the number of human body features according to the first target sample and the second target sample.

[0091] Through steps S321 to S323, the first target recognition for each frame of the image is performed based on the YOLOv5 algorithm and the second target recognition for each frame of the image is performed based on the CrowdCounting algorithm to reduce false detections and missed detections, and the final number of human features is combined with the first target sample and the second target sample to improve the accuracy of statistics.

[0092] See also Figure 8 , the present invention also discloses a device for identifying the number of people in a manned amusement equipment, comprising: an acquisition unit 10, a processing unit 20 and an identification unit 30;

[0093] An acquisition unit 10 is used to acquire a to-be-processed video corresponding to a target device and a running time of the target device;

[0094] A processing unit 20, configured to perform frame processing on the video to be processed based on a preset algorithm and the running time of the target device to obtain an image frame set;

[0095] The recognition unit 30 is used to perform human feature recognition on the image frame set, determine the number of people on the target device, and send the number of people to the background.

[0096] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned number recognition device for manned amusement equipment and each unit can refer to the corresponding description in the above-mentioned method embodiment, and for the convenience and simplicity of description, it will not be repeated here.

[0097] The above can be implemented in the form of a computer program, which can be used in Fig. 9 Runs on the computer device shown.

[0098] See also Fig. 9 , Fig. 9 is a schematic block diagram of a computer device provided in an embodiment of the present application; the computer device 500 may be a terminal or a server, wherein the terminal may be an electronic device with communication functions such as a smart phone, a tablet computer, a laptop computer, a desktop computer, a personal digital assistant, and a wearable device. The server may be an independent server or a server cluster composed of multiple servers.

[0099] See also Fig. 9 The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0100] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, which, when executed, can enable the processor 502 to execute a method for identifying the number of people in a manned amusement device, including the following steps: obtaining a to-be-processed video corresponding to a target device and the target device running time; performing frame processing on the to-be-processed video based on a preset algorithm and the target device running time to obtain an image frame set; performing human feature recognition on the image frame set to determine the number of people on the target device, and sending the number of people to the background.

[0101] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0102] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a method for identifying the number of people in a manned amusement device.

[0103] The network interface 505 is used to communicate with other devices over the network. Fig. 9 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0104] The processor 502 is used to run the computer program 5032 stored in the memory to implement the following steps:

[0105] Step S1, obtaining the to-be-processed video corresponding to the target device and the target device running time;

[0106] Step S2, processing the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set;

[0107] Step S3, performing human feature recognition on the image frame set, determining the number of people on the target device, and sending the number of people to the background.

[0108] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0109] It can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0110] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the above-mentioned method for identifying the number of people in a manned amusement device can be implemented. The storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the above-mentioned method can be implemented. The program instructions include the following steps:

[0111] Step S1, obtaining the to-be-processed video corresponding to the target device and the target device running time;

[0112] Step S2, processing the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set;

[0113] Step S3, performing human feature recognition on the image frame set, determining the number of people on the target device, and sending the number of people to the background.

[0114] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0115] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0116] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0117] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0119] The above embodiments are preferred implementation schemes of the present invention. In addition, the present invention may also be implemented in other ways. Any obvious replacement without departing from the concept of the present technical solution is within the protection scope of the present invention.

Claims

1. A method for identifying the number of people in an amusement device, characterized in that: The following steps are involved: Obtain the to-be-processed video corresponding to the target device and the target device running time; Processing the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set; Human body feature recognition is performed on the image frame set to determine the number of people on the target device, and the number of people is sent to the background.

2. The method for identifying the number of people in an amusement device according to claim 1, characterized in that: The step of performing frame processing on the video to be processed based on a preset algorithm and the target device running time to obtain an image frame set comprises: Obtaining a video reference time of the video to be processed; Extracting a target video from the video to be processed based on the video reference time and the target device running time; The target video is frame-processed based on the preset algorithm to obtain an image frame set.

3. The method for identifying the number of people in an amusement device according to claim 2, characterized in that: The step of performing frame processing on the target video based on the preset algorithm to obtain an image frame set comprises: Splitting the target video into multiple sub-videos based on the preset algorithm; Segmenting the plurality of sub-videos based on a preset frame interval to obtain sliced ​​videos; Feature extraction is performed on each of the segmented videos to obtain an image frame set.

4. The method for identifying the number of people in an amusement device according to claim 3, characterized in that: The step of extracting features from each of the video segments to obtain an image frame set comprises: Decomposing each of the segmented videos to obtain a set of video frames; A target frame image is selected from the video frame set, and features are extracted from the target frame image and adjacent frame images to obtain an image frame set.

5. The method for identifying the number of people in an amusement device according to claim 1, characterized in that: The step of performing human feature recognition on the image frame set to determine the number of people on the target device comprises: Extracting boundary features of each frame of the image in the image frame set to determine a boundary box corresponding to each frame of the image; Determine the number of human features in each frame of the image based on the bounding box; The number of people on the target device is determined based on the number of human body features.

6. The method for identifying the number of people in an amusement device according to claim 5, characterized in that: The step of extracting boundary features from each frame of the image in the image frame set and determining a boundary box corresponding to each frame of the image comprises: Determine the target area of ​​each frame of the image, and mark the target area with a target angle; The marked target area is processed based on a neural network to obtain the bounding box.

7. The method for identifying the number of people in an amusement device according to claim 5, characterized in that: The step of the number of human features in each frame image based on the boundary data comprises: Performing first target recognition on each frame of the image based on the bounding box and the YOLOV5 algorithm to obtain a first target sample; Based on the bounding box and the CrowdCounting algorithm, a second target is identified on each frame of the picture to obtain a second target sample; The number of human body features is determined according to the first target sample and the second target sample.

8. A device for identifying the number of people in an amusement ride, characterized in that: include: an acquisition unit, a processing unit and an identification unit; The acquisition unit is used to acquire the to-be-processed video corresponding to the target device and the target device running time; The processing unit is used to process the video to be processed frame by frame based on a preset algorithm and the running time of the target device to obtain an image frame set; The recognition unit is used to perform human feature recognition on the image frame set, determine the number of people on the target device, and send the number of people to the background.

9. A computer device, characterized in that: The computer device includes a memory and a processor, a computer program is stored on the processor, and when the processor executes the computer program, the method for identifying the number of people in an amusement device according to any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the method for identifying the number of people in an amusement device as described in any one of claims 1 to 7 can be implemented.

Images