Operation control method and system for automobile training

Abstract

The present invention discloses an operation control method and system in automobile training, which comprises the following steps: determining an action picture of a trainee based on an action path of the trainee; matching the action picture of the trainee with a current automobile training scene to freeze the picture to be corrected; determining a region to be corrected according to the picture to be corrected, and triggering a correction prompt based on the region to be corrected; defining an operation control point of the trainee according to the correction prompt, and defining an operation variation of the operation control point; triggering a posture adjustment of the trainee according to the operation control point of the trainee and the corresponding operation variation, at which time, matching the current automobile training scene with respect to the action picture of the trainee, and performing correction processing on the action picture of the trainee so as to freeze the picture to be corrected, thereby providing a correction prompt for the action picture of the trainee, and at the same time, defining the operation variation of the operation control point, thereby realizing the posture adjustment of the trainee, and being able to correct the action habit of the trainee in time.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile training, and in particular to an operation control method and system for automobile training. Background Art

[0002] With the development of science and technology, automobile training is applied to vocational teaching and as a practical training project, the trainees enter the training room and are in the automobile training scene. The trainees load and unload, assemble and perform other steps on automobile parts according to the course requirements. At this time, the trainees form action pictures with their hand movements and perform actions according to the diagrams. However, there are some actions in the trainees' action pictures that need to be corrected, and no corresponding correction prompts and posture adjustments are given. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides an operation control method and system under automobile training, which matches the trainee's action picture with the current automobile training scene, and corrects the trainee's action picture so as to freeze the picture to be corrected, thereby providing correction prompts for the trainee's action picture. At the same time, the operation change amount of the operation control point is defined, thereby realizing the trainee's posture adjustment and being able to correct the trainee's action habits in time.

[0004] In order to solve the above technical problems, an embodiment of the present invention provides an operation control method under automobile training, which is applied to automobile training scenarios;

[0005] The operation control method under the automobile training comprises:

[0006] In the automobile training scenario, the trainee’s action path is collected;

[0007] Determine the action picture of the trainee based on the action path of the trainee;

[0008] Match the trainee's action picture with the current automobile training scene to freeze the picture to be corrected;

[0009] Determine the area to be corrected according to the picture to be corrected, and trigger a correction prompt based on the area to be corrected;

[0010] Define the trainee's operation control point according to the correction prompt, and define the operation change amount of the operation control point;

[0011] The trainee's posture adjustment is triggered according to the trainee's operation control point and the corresponding operation change.

[0012] Optionally, in the automobile training scenario, collecting the trainee's motion path includes:

[0013] Get the trainee's position;

[0014] Compare the trainee's positioning with the positioning of the vehicle training scene, and guide the trainee into the vehicle training scene;

[0015] When the trainee enters the automobile training scene, the trainee's spatial position is collected and the trainee's spatial position in the automobile training scene is determined;

[0016] According to the spatial position of the trainee in the automobile training scene, the directions of the surrounding cameras are adjusted so that the directions of multiple cameras converge on the trainee;

[0017] Cameras in different directions collect action images of the trainee, and determine the action path of the trainee based on multiple action images.

[0018] Optionally, determining the trainee's action picture based on the trainee's action path includes:

[0019] Simplify the trainee's activity points based on the trainee's hands;

[0020] Based on the trainee's activity point, the trainee moves along the trainee's motion path and detects the trainee's motion path;

[0021] In the process of detecting the trainee's motion path, the spatial position of the trainee's activity point in each time period is collected;

[0022] The trainee's action picture is determined according to the spatial position of the trainee's activity point in each time period.

[0023] Optionally, matching the trainee's action picture with the current automobile training scene to freeze the picture to be corrected includes:

[0024] Traverse the trainee's action screen;

[0025] Form a simplified picture based on the spatial position of the trainee's action picture;

[0026] Embed the simplified images into the current automotive training scene and match them.

[0027] Optionally, the matching of the trainee's action picture with the current automobile training scene to freeze the picture to be corrected also includes:

[0028] In the process of matching the simplified picture with the current automobile training scene, each position point in the simplified picture is measured and the position offset is defined;

[0029] Positioning and correcting the position point according to the comparison between the position offset and the preset position offset;

[0030] Freeze the image to be corrected according to the correction position point.

[0031] Optionally, determining the area to be corrected according to the picture to be corrected, and triggering a correction prompt based on the area to be corrected, includes:

[0032] Get the picture to be corrected;

[0033] Traverse the image to be corrected and locate the offset point where the position offset exists;

[0034] Perform distance association based on multiple offset points to locate a set that meets a preset distance;

[0035] Constructing a region to be corrected based on a set that meets a preset distance;

[0036] Input the area to be corrected into the area learning model and determine the area type;

[0037] Trigger corresponding correction prompts according to the area type.

[0038] Optionally, the step of defining the trainee's operation control point according to the correction prompt and defining the operation change amount of the operation control point includes:

[0039] Collect correction tips;

[0040] Traverse the correction prompts and extract the limb names in the correction prompts;

[0041] Word detection is performed based on the location of the body limb name, and the action words associated with the body limb name are fixed;

[0042] Define the trainee's operation control points according to limb names and action words.

[0043] Optionally, the step of defining the trainee's operation control point according to the correction prompt and defining the operation change amount of the operation control point also includes:

[0044] Traverse the operation control points and determine the number of the operation control points;

[0045] The operation control points are sequentially associated along the upper and lower relationships, and a collaborative relationship between multiple adjacent operation control points is established;

[0046] Construct corrective actions based on the number of operation control points and their collaborative relationships, and define the operational changes of the operation control points.

[0047] Optionally, triggering the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount includes:

[0048] Obtain the trainee's operation control points and corresponding operation changes;

[0049] Define the direction of the operation control point according to the vector corresponding to the operation change;

[0050] The trainee's posture adjustment is triggered based on the direction of the operation control point and the operation change amount. At this time, the trainee's posture adjustment sequence is triggered according to the cooperative relationship of each operation control point.

[0051] In addition, an embodiment of the present invention further provides an operation control system for automobile training, wherein the operation control system for automobile training comprises:

[0052] The acquisition module is used to collect the trainee's motion path in the automobile training scene;

[0053] An action picture module, used for determining the action picture of the trainee based on the action path of the trainee;

[0054] A matching module is used to match the trainee's action picture with the current automobile training scene to freeze the picture to be corrected;

[0055] A correction prompt module, used to determine the area to be corrected according to the picture to be corrected, and trigger a correction prompt based on the area to be corrected;

[0056] A definition module is used to define the trainee's operation control point according to the correction prompt and define the operation change amount of the operation control point;

[0057] The adjustment module is used to trigger the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount.

[0058] In an embodiment of the present invention, through the method in the embodiment of the present invention, the trainee's action path is collected; the trainee's action picture is determined based on the trainee's action path; the trainee's action picture is matched with the current automobile training scene to freeze the picture to be corrected; the area to be corrected is determined according to the picture to be corrected, and the correction prompt is triggered based on the area to be corrected; the trainee's operation control point is defined according to the correction prompt, and the operation change amount of the operation control point is defined; the trainee's posture adjustment is triggered according to the trainee's operation control point and the corresponding operation change amount. At this time, the current automobile training scene is matched with the trainee's action picture, and the trainee's action picture is corrected so as to freeze the picture to be corrected, thereby providing a correction prompt for the trainee's action picture. At the same time, the trainee's operation control point is defined according to the correction prompt, and the operation change amount of the operation control point is defined, thereby realizing the trainee's posture adjustment, ensuring that the trainee's action is prompt-controlled, and the trainee's action habits can be corrected in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 is a flow chart of an operation control method in automobile training in an embodiment of the present invention;

[0061] Figure 2 is a flow chart of S11 in the operation control method under automobile training in an embodiment of the present invention;

[0062] Figure 3 is a flow chart of S12 in the operation control method under automobile training in an embodiment of the present invention;

[0063] Figure 4 is a flow chart of S13 in the operation control method under automobile training in an embodiment of the present invention;

[0064] Figure 5 is a flow chart of S14 in the operation control method under automobile training in an embodiment of the present invention;

[0065] Figure 6 is a flow chart of S15 in the operation control method under automobile training in an embodiment of the present invention;

[0066] Figure 7 It is a schematic diagram of the structure of the operation control system in the automobile training in an embodiment of the present invention;

[0067] Figure 8 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0068] 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 only 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.

[0069] Example

[0070] See also Figures 1 to 8 , an operation control method for automobile training, applied to automobile training scenarios; the operation control method for automobile training includes:

[0071] Step S11: In the automobile training scene, collecting the trainee's action path;

[0072] Step S12: determining the trainee's action picture based on the trainee's action path;

[0073] Step S13: matching the trainee's action picture with the current automobile training scene to freeze the picture to be corrected;

[0074] Step S14: determining the area to be corrected according to the picture to be corrected, and triggering a correction prompt based on the area to be corrected;

[0075] Step S15: defining the trainee's operation control point according to the correction prompt, and defining the operation change amount of the operation control point;

[0076] Step S16: triggering the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount.

[0077] In an embodiment of the present invention, through the method in the embodiment of the present invention, the trainee's action picture is determined based on the trainee's action path; the trainee's action picture is matched with the current automobile training scene to freeze the picture to be corrected; the area to be corrected is determined according to the picture to be corrected, and the correction prompt is triggered based on the area to be corrected; the trainee's operation control point is defined according to the correction prompt, and the operation change amount of the operation control point is defined; the trainee's posture adjustment is triggered according to the trainee's operation control point and the corresponding operation change amount. At this time, the current automobile training scene is matched with the trainee's action picture, and the trainee's action picture is corrected so as to freeze the picture to be corrected, thereby giving a correction prompt to the trainee's action picture. At the same time, the operation change amount of the operation control point is defined, so as to realize the trainee's posture adjustment and correct the trainee's action habits in time.

[0078] In step S11, in the automobile training scene, the trainee's action path is collected;

[0079] In an embodiment of the present application, the trainee enters a training room and is in a car training scene. The training room has multiple cameras and monitors the trainees in the car training scene in real time. At this time, the trainees' hand movements are captured by multiple cameras, and the trainees' movement paths are collected. The trainees' movement paths are the movement trajectories of the trainees' hands.

[0080] In the specific implementation process of the present invention, the specific steps may be:

[0081] S111: Obtain the trainee's location;

[0082] S112: Compare the positioning of the trainee with the positioning of the automobile training scene, and guide the trainee to enter the automobile training scene;

[0083] In an embodiment of the present application, before the trainee enters the training room, the trainee is tracked in order to define the trainee's position, thereby obtaining the trainee's position. At this time, the trainee's position and the positioning of the automobile training scene are introduced, so as to compare the trainee's position with the positioning of the automobile training scene, thereby defining the relative position between the trainee and the automobile training scene, and then guiding the trainee to enter the automobile training scene, ensuring the positioning matching between the trainee and the automobile training scene.

[0084] S113: When the trainee enters the automobile training scene, the spatial position of the trainee is collected, and the spatial position of the trainee in the automobile training scene is determined;

[0085] S114: adjusting the directions of the surrounding cameras according to the spatial position of the trainee in the automobile training scene, so that the directions of the multiple cameras converge on the trainee;

[0086] S115: collecting motion images of the trainee based on cameras in different directions, and determining the motion path of the trainee according to the multiple motion images;

[0087] In an embodiment of the present application, when a trainee enters a car training scene, the trainee's spatial position is collected, and the trainee's spatial position in the car training scene is determined. By controlling the trainee's spatial position in the car training scene, it is convenient to control the trainee's spatial position, so as to adjust the directions of surrounding cameras according to the trainee's spatial position in the car training scene, so that the directions of multiple cameras converge on the trainee, and the trainee is monitored in multiple different directions, thereby collecting the trainee's motion images based on cameras in different orientations, and determining the trainee's motion path based on multiple motion images.

[0088] In step S12, the trainee's action picture is determined based on the trainee's action path;

[0089] In an embodiment of the present application, the trainee's motion path is collected and controlled, so as to determine the trainee's motion picture based on the trainee's motion path, ensure the trainee's motion picture, and then perform subsequent processing on the trainee's motion picture.

[0090] In the specific implementation process of the present invention, the specific steps may be:

[0091] S121: Simplify the trainee's activity points based on the trainee's hands;

[0092] S122: moving along the motion path of the trainee based on the activity point of the trainee, and detecting the motion path of the trainee;

[0093] S123: during the detection of the trainee's motion path, collecting the spatial positions of the trainee's activity points in each time period;

[0094] S124: Determine the action picture of the trainee according to the spatial position of the trainee's activity point in each time period.

[0095] In an embodiment of the present application, the trainee's activity points are controlled. At this time, the trainee's activity points are simplified based on the trainee's hands, and monitoring is performed along the trainee's activity points, so that the trainee's movement path is moved based on the trainee's activity points, and the trainee's movement path is detected, thereby ensuring the integrity of the trainee's movement path.

[0096] In addition, during the detection of the trainee's motion path, the spatial positions of the trainee's activity points in each time period are collected, and the spatial positions of the trainee's activity points in each time period are located, thereby ensuring the accuracy of the spatial positions of the trainee's activity points in each time period, so as to facilitate the subsequent association of the spatial positions of the trainee's activity points in each time period. Therefore, the trainee's motion picture is determined according to the spatial positions of the trainee's activity points in each time period.

[0097] In step S13, the trainee's action picture is matched with the current automobile training scene to freeze the picture to be corrected;

[0098] In an embodiment of the present application, the trainee's action picture and the current automobile training scene are obtained, and a matching comparison is performed between the trainee's action picture and the current automobile training scene, so that the picture to be corrected can be frozen under the analysis between the trainee's action picture and the current automobile training scene, and then the picture to be corrected is processed, so as to extend subsequent correction prompts, thereby realizing the key processing of the local picture.

[0099] In the specific implementation process of the present invention, the specific steps may be:

[0100] S131: traverse the trainee's action screen;

[0101] S132: forming a simplified picture based on the spatial position of the trainee's action picture;

[0102] S133: embedding the simplified picture into the current automobile training scene and matching them;

[0103] In an embodiment of the present application, the trainee's action screen is traversed to facilitate the integrity check of the trainee's action screen. At the same time, a simplified screen is formed based on the spatial position of the trainee's action screen to grasp the trainee's activity point, so as to facilitate control based on the simplified screen, reduce processing requirements, and ensure the integrity of the action path. At this time, the simplified screen is embedded in the current automobile training scene and matched.

[0104] S134: During the matching process between the simplified picture and the current automobile training scene, each position point in the simplified picture is measured and a position offset is defined;

[0105] S135: Locating and correcting the position point according to the comparison between the position offset and the preset position offset;

[0106] S136: Freeze the image to be corrected according to the correction position point.

[0107] Among them, the matching process of the simplified picture and the current automobile training scene is monitored, so as to control the matching process of the simplified picture and the current automobile training scene. At this time, each position point in the simplified picture is measured, and the distance between each position point in the simplified picture and the preset position point is compared, so as to define the position offset, so as to locate the degree of offset through the position offset, and then locate the correction position point according to the comparison between the position offset and the preset position offset, so as to freeze the picture to be corrected according to the correction position point, thereby ensuring the accuracy of the picture to be corrected.

[0108] S14: determining a region to be corrected according to the image to be corrected, and triggering a correction prompt based on the region to be corrected;

[0109] In an embodiment of the present application, the trainee's action picture is matched with the current automobile training scene, and the trainee's action picture is corrected so as to freeze the picture to be corrected, thereby providing a correction prompt for the trainee's action picture.

[0110] In the specific implementation process of the present invention, the specific steps may be:

[0111] S141: Acquire the picture to be corrected;

[0112] S142: traverse the picture to be corrected and locate the offset point where the position offset exists;

[0113] In an embodiment of the present application, a picture to be corrected is obtained and managed. At this time, the picture to be corrected is traversed and offset points with position offsets are located to facilitate further processing based on the offset points, thereby marking each offset point.

[0114] S143: performing distance association based on multiple offset points to locate a set that meets a preset distance;

[0115] S144: constructing a region to be corrected based on a set that meets a preset distance;

[0116] S145: inputting the region to be corrected into the region learning model and determining the region type;

[0117] S146: triggering a corresponding correction prompt according to the area type;

[0118] In an embodiment of the present application, multiple offset points are frozen to facilitate distance association based on the multiple offset points, thereby performing distance control on multiple adjacent offset points, and then locating a set that meets the preset distance, thereby performing regional control on the offset points that meet the requirements, and then constructing a to-be-corrected area based on the set that meets the preset distance.

[0119] Furthermore, the area to be corrected is input into the area learning model, which is trained based on the previous areas to be corrected and area types, so that the area to be corrected can be intelligently identified according to the area learning model, and the corresponding area type can be output based on the area learning model, so as to determine the area type, and then the mapping table can be compared along the area type, and the corresponding correction prompt can be triggered according to the area type, so as to ensure the adaptability of the correction prompt, thereby controlling multiple areas to be corrected and improving the versatility of use.

[0120] S15: defining the trainee's operation control point according to the correction prompt, and defining the operation change amount of the operation control point;

[0121] In the specific implementation process of the present invention, the specific steps may be:

[0122] S151: Collect correction prompts;

[0123] S152: traverse the correction prompts and extract the limb names in the correction prompts;

[0124] S153: Detecting words based on the positions of the body limb names, and determining action words associated with the body limb names;

[0125] In an embodiment of the present application, the correction prompts are further processed to facilitate traversal of the correction prompts and extraction of the limb names in the correction prompts. At this time, the names in the correction prompts are screened and the limb names in the correction prompts are located, so that word detection is performed based on the locations of the limb names, and the action words associated with the limb names are frozen, and then the limb names and action words are quickly screened, ensuring the subsequent processing of the limb names and action words.

[0126] S154: Define the trainee's operation control points according to the body names and action words;

[0127] S155: traversing the operation control points and determining the number of the operation control points;

[0128] S156: sequentially associating the operation control points along the upper and lower relationships, and establishing a collaborative relationship between multiple adjacent operation control points;

[0129] S157: Construct a corrective action according to the number of operation control points and the collaborative relationship, and define the operation change amount of the operation control points.

[0130] In an embodiment of the present application, the trainee's operation control point is defined according to the limb name and action word, for example, the limb name is wrist, the action word is raise, and the trainee's operation control point is the top point of the wrist, and multiple correction prompts are controlled in sequence, thereby freezing multiple trainees' operation control points, and then determining the number of operation control points, so as to facilitate overall regulation based on the number of operation control points, and further, constructing a correction action according to the number of operation control points and the collaborative relationship, and defining the operation change amount of the operation control point for the correction action, so as to clarify the range of the change. Furthermore, the operation change amount of the operation control point is defined, so as to achieve the trainee's posture adjustment and timely correct the trainee's movement habits.

[0131] S16: triggering the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount;

[0132] At this time, the trainee's operation control point and the corresponding operation change are obtained; S162: the direction of the operation control point is defined according to the vector corresponding to the operation change; the trainee's posture adjustment is triggered based on the direction of the operation control point and the operation change. At this time, the trainee's posture adjustment sequence is triggered according to the cooperative relationship of each operation control point. At the same time, the operation change of the operation control point is defined, so as to realize the trainee's posture adjustment and correct the trainee's movement habits in time.

[0133] In an embodiment of the present invention, through the method in the embodiment of the present invention, the trainee's action picture is determined based on the trainee's action path; the trainee's action picture is matched with the current automobile training scene to freeze the picture to be corrected; the area to be corrected is determined according to the picture to be corrected, and the correction prompt is triggered based on the area to be corrected; the trainee's operation control point is defined according to the correction prompt, and the operation change amount of the operation control point is defined; the trainee's posture adjustment is triggered according to the trainee's operation control point and the corresponding operation change amount. At this time, the current automobile training scene is matched with the trainee's action picture, and the trainee's action picture is corrected so as to freeze the picture to be corrected, thereby giving a correction prompt to the trainee's action picture. At the same time, the operation change amount of the operation control point is defined, so as to realize the trainee's posture adjustment and correct the trainee's action habits in time.

[0134] Example

[0135] See also Figure 7 , Figure 7 It is a schematic diagram of the structural composition of the operation control system for automobile training in an embodiment of the present invention.

[0136] like Figure 7 As shown, an operation control system for automobile training, the operation control system for automobile training comprises:

[0137] The collection module 21 is used to collect the trainee's motion path in the automobile training scene;

[0138] An action picture module 22, for determining an action picture of the trainee based on the action path of the trainee;

[0139] A matching module 23 is used to match the trainee's action picture with the current automobile training scene to freeze the picture to be corrected;

[0140] A correction prompt module 24, used to determine the area to be corrected according to the picture to be corrected, and trigger a correction prompt based on the area to be corrected;

[0141] A definition module 25, used to define the trainee's operation control point according to the correction prompt, and define the operation change amount of the operation control point;

[0142] The adjustment module 26 is used to trigger the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount.

[0143] Example

[0144] See also Figure 8 , refer to the following Figure 8 The electronic device 40 according to this embodiment of the present invention will be described. Figure 8The electronic device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0145] like Figure 8 As shown, the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0146] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0147] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0148] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0149] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0150] The electronic device 40 may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 40, and / or any device that enables the electronic device 40 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 45. Figure 8 As shown, the network adapter 45 communicates with other modules of the electronic device 40 via the bus 43. It should be understood that although Figure 8Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems.

[0151] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0152] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. In addition, it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the above method.

[0153] In addition, the above describes in detail the operation control method and system for automobile training provided by the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An operation control method for automobile training, characterized in that: Applied to automobile training scenarios; The operation control method under the automobile training comprises: In the automobile training scenario, the trainee’s action path is collected; Determine the action picture of the trainee based on the action path of the trainee; Match the trainee's action picture with the current automobile training scene to freeze the picture to be corrected; Determine the area to be corrected according to the picture to be corrected, and trigger a correction prompt based on the area to be corrected; Define the trainee's operation control point according to the correction prompt, and define the operation change amount of the operation control point; Trigger the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change; The matching of the trainee's action picture with the current automobile training scene to freeze the picture to be corrected includes: Traverse the trainee's action screen; Form a simplified picture based on the spatial position of the trainee's action picture; Embed the simplified images into the current automobile training scene and match them; In the process of matching the simplified picture with the current automobile training scene, each position point in the simplified picture is measured and the position offset is defined; Positioning and correcting the position point according to the comparison between the position offset and the preset position offset; Freeze the image to be corrected according to the correction position point.

2. The operation control method for automobile training according to claim 1, characterized in that: In the automobile training scenario, collecting the trainee's action path includes: Get the trainee's position; Compare the trainee's positioning with the positioning of the vehicle training scene, and guide the trainee into the vehicle training scene; When the trainee enters the automobile training scene, the trainee's spatial position is collected and the trainee's spatial position in the automobile training scene is determined; According to the spatial position of the trainee in the automobile training scene, the directions of the surrounding cameras are adjusted so that the directions of multiple cameras converge on the trainee; Cameras in different directions collect action images of the trainee, and determine the action path of the trainee based on multiple action images.

3. The operation control method for automobile training according to claim 1, characterized in that: The step of determining the trainee's action picture based on the trainee's action path includes: Simplify the trainee's activity points based on the trainee's hands; Based on the trainee's activity point, the trainee moves along the trainee's motion path and detects the trainee's motion path; In the process of detecting the trainee's motion path, the spatial position of the trainee's activity point in each time period is collected; The trainee's action picture is determined according to the spatial position of the trainee's activity point in each time period.

4. The operation control method for automobile training according to claim 1, characterized in that: The determining the area to be corrected according to the picture to be corrected, and triggering a correction prompt based on the area to be corrected, includes: Get the picture to be corrected; Traverse the image to be corrected and locate the offset point where the position offset exists; Perform distance association based on multiple offset points to locate a set that meets a preset distance; Constructing a region to be corrected based on a set that meets a preset distance; Input the area to be corrected into the area learning model and determine the area type; Trigger corresponding correction prompts based on the area type.

5. The operation control method for automobile training according to claim 4 is characterized in that: Defining the trainee's operation control point according to the correction prompt and defining the operation change amount of the operation control point includes: Collect correction tips; Traverse the correction prompts and extract the limb names in the correction prompts; Word detection is performed based on the location of the body limb name, and the action words associated with the body limb name are fixed; Define the trainee's operation control points according to limb names and action words.

6. The operation control method for automobile training according to claim 5, characterized in that: The step of defining the trainee's operation control point according to the correction prompt and defining the operation change amount of the operation control point also includes: Traverse the operation control points and determine the number of the operation control points; The operation control points are sequentially associated along the upper and lower relationships, and a collaborative relationship between multiple adjacent operation control points is established; Construct corrective actions based on the number of operation control points and their collaborative relationships, and define the operational changes of the operation control points.

7. The operation control method for automobile training according to claim 6, characterized in that: The triggering of the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount includes: Obtain the trainee's operation control points and corresponding operation changes; Define the direction of the operation control point according to the vector corresponding to the operation change; The trainee's posture adjustment is triggered based on the direction of the operation control point and the operation change amount. At this time, the trainee's posture adjustment sequence is triggered according to the cooperative relationship of each operation control point.

8. An operation control system for automobile training, characterized in that: The operation control system for vehicle training is applied to the operation control method for vehicle training as claimed in any one of claims 1 to 7, and the operation control system for vehicle training includes: The acquisition module is used to collect the trainee's motion path in the automobile training scene; An action picture module, used for determining the action picture of the trainee based on the action path of the trainee; A matching module is used to match the trainee's action picture with the current automobile training scene to freeze the picture to be corrected; A correction prompt module, used to determine the area to be corrected according to the picture to be corrected, and trigger a correction prompt based on the area to be corrected; A definition module is used to define the trainee's operation control point according to the correction prompt and define the operation change amount of the operation control point; The adjustment module is used to trigger the trainee's posture adjustment according to the trainee's operation control point and the corresponding operation change amount.

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