A method, system, device and medium for determining airbag deployment rate

Abstract

The present application provides a method, system, device and medium for determining an airbag deployment rate, which relates to the technical field of automobile collision testing, including: decomposing an airbag deployment video into multiple first images according to a first preset time sequence; calculating a first ratio according to a circular mark on a dummy's head in the first image; processing the first images one by one in time sequence, extracting feature points of each first image according to position information of the airbag contour line of each first image, and calculating the airbag deployment rate at each moment within a first preset time through the X-axis extreme value points, Y-axis extreme value points and the first ratio of two adjacent first images; it can be seen from the above steps that the present application realizes accurate recognition of irregular edges during the airbag deployment process, so as to accurately calculate the distance and speed in all directions during the airbag deployment process, and improve the stability of the vehicle's judgment on the dangerous deployment of the airbag in the collision test; no manual operation by the evaluator is required throughout the process, thereby improving the test efficiency and avoiding test errors.

Description

Technical Field

[0001] The present application relates to the technical field of automobile collision testing, and in particular to a method, system, device and medium for determining an airbag deployment rate. Background Art

[0002] In recent years, the automobile industry has developed rapidly. As a safety auxiliary tool for automobiles, the emergence of airbags has greatly reduced the mortality rate. Therefore, it is necessary to ensure that their size is accurate and they can be used normally, and do not cause harm to the human face when deployed. Therefore, it is necessary to judge whether the airbags are deployed dangerously during the vehicle collision test.

[0003] In the prior art, it is only possible to approximately determine whether the airbag deployment speed exceeds the specified value through experiments, and it is impossible to accurately obtain the specific airbag deployment speed value, resulting in the inability to improve the stability of the airbag dangerous deployment judgment in the vehicle collision test. At the same time, the entire operation process is completed manually by the evaluators, which is inefficient and easily leads to errors and differences in evaluation results due to human identification. Summary of the invention

[0004] The purpose of this application is to address the above problems and provide a method, system, device and medium for determining an airbag deployment rate, so as to improve the stability of the judgment of airbag dangerous deployment in vehicle collision testing.

[0005] In a first aspect, the present application provides a method for determining an airbag deployment rate, comprising the following steps:

[0006] S100: Decomposing the airbag deployment video into a plurality of first images according to a first preset time sequence;

[0007] S200: Calculating a first ratio M according to the circular mark on the dummy's head in the first image; the first ratio is a ratio of the image moving distance to the actual moving distance;

[0008] S300: Processing all the first images one by one in chronological order to obtain position information of the airbag contour line of each of the first images;

[0009] S400: extracting feature points of each of the first images according to the position information of the airbag contour line of each of the first images; the feature points include: an X-axis extreme point and a Y-axis extreme point;

[0010] S500: Calculate the X-axis airbag deployment rate, the Y-axis airbag deployment rate and the combined deployment rate at each moment within the first preset time according to the X-axis extreme value points, the Y-axis extreme value points and the first ratio of two adjacent first images.

[0011] According to the technical solution provided by this application, step S200 also includes the following steps:

[0012] S201: Identify a circular mark on the dummy's head in any of the first images, and obtain an image diameter of the circular mark;

[0013] S202: according to the image diameter of the circular mark and actual diameter , use formula (1) to calculate the first ratio M;

[0014] Formula (I).

[0015] According to the technical solution provided by this application, step S500 includes the following steps:

[0016] S501: Subtract the X-axis extreme value points of two adjacent first images to obtain the X-axis image movement distance of the two adjacent first images. ;

[0017] S502: Moving distance according to the X-axis image And the first ratio M, using formula (ii) to calculate the actual moving distance of the X axis within the first preset time ;

[0018] Formula (II);

[0019] S503: Based on the actual moving distance of the X-axis within the first preset time , use formula (III) to calculate the airbag deployment rate on the X axis ;

[0020] Formula (III);

[0021] in: T is the first preset time;

[0022] S504: Subtract the Y-axis extreme value points of two adjacent first images to obtain the Y-axis image movement distance of the two adjacent first images. ;

[0023] S505: moving the image according to the Y-axis distance And the first ratio M, the actual moving distance of the Y axis within the first preset time is calculated using formula (IV) ;

[0024] Formula (IV);

[0025] S506: According to the actual moving distance of the Y axis within the first preset time , use formula (5) to calculate the airbag deployment rate on the Y axis ;

[0026] Formula (V);

[0027] S507: Airbag deployment rate according to the X-axis and the airbag deployment rate on the Y axis , use formula (VI) to calculate the combined expansion rate ;

[0028] Formula (VI).

[0029] According to the technical solution provided by the present application, the following steps are also included before step S100:

[0030] S001: Acquire a target video, capture a segment from when the airbag starts to pop out to when the airbag area is maximized, and obtain the airbag deployment video; the target video is a continuous video from a first moment to a second moment, the first moment is the moment before the airbag starts to pop out, and the second moment is the moment after the airbag area is maximized.

[0031] According to the technical solution provided by the present application, the following steps are also included after S500:

[0032] S600: Storing and outputting the airbag deployment rate of the X axis corresponding to each moment within the first preset time , Y-axis airbag deployment rate and the combined expansion rate .

[0033] According to the technical solution provided in the present application, when the airbag deployment video is decomposed into a plurality of first pictures according to a first preset time sequence, the sizes of the first pictures are the same.

[0034] In a second aspect, the present application provides an airbag deployment rate determination system, comprising:

[0035] A first processing module, the first processing module is used to decompose the airbag deployment video into a plurality of first pictures according to a first preset time sequence;

[0036] A second processing module, the second processing module is used to process all the first images one by one in chronological order to obtain position information of the airbag contour line of each of the first images;

[0037] The third processing module is used to calculate the first ratio M according to the circular mark on the dummy's head in the first picture; the first ratio is the ratio of the image distance to the actual distance; and according to the position information of the airbag contour line of each first picture, extract the feature points of each first picture, the feature points include: X-axis extreme point and Y-axis extreme point; according to the X-axis extreme point, Y-axis extreme point and the first ratio of two adjacent first pictures, respectively calculate the X-axis airbag deployment rate, Y-axis airbag deployment rate and combined deployment rate at each moment within the first preset time.

[0038] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the airbag deployment rate determination method as described above when executing the computer program.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the airbag deployment rate determination method as described above is implemented.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] The present application provides a method for determining an airbag deployment rate. First, an airbag deployment video is decomposed into a plurality of first images according to a first preset time sequence; a first ratio is calculated according to a circular mark on a dummy head in the first image; all the first images are processed one by one according to the time sequence to obtain position information of an airbag contour line of each first image; and feature points of each first image are extracted according to the position information of the airbag contour line of each first image, wherein the feature points include: an X-axis extreme value point and a Y-axis extreme value point, and the first ratio is calculated by using the X-axis extreme value points, the Y-axis extreme value points and the first ratio of two adjacent first images. Assume the X-axis airbag deployment rate, Y-axis airbag deployment rate and combined deployment rate at each moment in time; through the above steps, it can be seen that the present application processes all the first images one by one in chronological order to identify the airbag contour line, thereby realizing accurate identification of irregular edges during the airbag deployment process, so as to accurately calculate the distance and speed in all directions during the airbag deployment process, and at the same time calculate the real-time area of ​​the airbag; the present application realizes non-contact detection, and no manual operation of the evaluator is required throughout the process, thereby avoiding errors and differences in evaluation results caused by human identification, thereby improving the stability, test efficiency and accuracy of the vehicle's judgment on the dangerous deployment of airbags in collision tests.

[0042] It should be understood that the description of technical features, technical solutions, beneficial effects or similar language in this application does not imply that all features and advantages can be realized in any single embodiment. On the contrary, it is understood that the description of features or beneficial effects means that specific technical features, technical solutions or beneficial effects are included in at least one embodiment. Therefore, the description of technical features, technical solutions or beneficial effects in this specification does not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions and beneficial effects described in the present embodiment can also be combined in any appropriate manner. Those skilled in the art will understand that the embodiment can be realized without one or more specific technical features, technical solutions or beneficial effects of a specific embodiment. In other embodiments, additional technical features and beneficial effects can also be identified in a specific embodiment that does not embody all embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solution in this embodiment, the drawings required for use in the description of the embodiment will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A flow chart of a method for determining an airbag deployment rate provided in an embodiment of the present application;

[0045] Figure 2 A schematic diagram of an airbag deployment rate determination system provided in an embodiment of the present application;

[0046] Figure 3 An airbag deployment rate curve diagram provided in an embodiment of the present application;

[0047] Figure 4 A schematic diagram of a computer system of an electronic device provided in an embodiment of the present application.

[0048] In the figure: 1. first acquisition module; 2. first processing module; 3. second processing module; 4. third processing module; 5. first storage module; 6. first identification module; 401. CPU; 402. ROM; 403. RAM; 404. bus; 405. I / O interface; 406. input part; 407. output part; 408. storage part; 409. communication part; 410. drive; 411. removable medium. DETAILED DESCRIPTION

[0049] In order to enable those skilled in the art to better understand the technical solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings. The description in this section is only exemplary and explanatory and should not have any limiting effect on the protection scope of the present application. Specifically, the described embodiments are only embodiments of a part of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work should fall within the scope of protection of the present application.

[0050] It should be noted that similar reference numerals and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0051] In order to facilitate the understanding of this application, a brief introduction to the related technology is first given:

[0052] The airbag deployment speed is a variable that changes with the airbag deployment process. In the early stage of detonation, the airbag needs to break through the restraint of the LOGO cover or the dashboard skin, and high speed is required to ensure sufficient functions. After that, the airbag deployment speed decreases as it moves backward. Since the head area and the area behind it cover the positions of most occupants' heads, it is more reasonable to examine the airbag deployment speed in the head area. The China New Car Assessment Program also introduced an airbag hazard deployment evaluation project in the 2021 version, which is applicable to the full-width frontal rigid barrier collision test and the 50% overlapping moving progressive deformation barrier collision test. It is necessary to examine whether the airbag deployment speed in the head area of ​​the front dummy exceeds 90m / s. In the existing technology, it can only be approximately determined through experiments whether the airbag deployment speed exceeds 90m / s, and the specific airbag deployment speed value cannot be accurately obtained, resulting in the inability to improve the stability of the judgment of airbag hazard deployment in vehicle collision tests. At the same time, the entire operation process is completed manually by the evaluators, which is inefficient.

[0053] In view of this, an embodiment of the present application provides a method for determining an airbag deployment rate. The method first decomposes the airbag deployment video in chronological order to obtain multiple first images, and then processes all the first images one by one in chronological order to identify the airbag contour line, thereby achieving accurate identification of irregular edges during the airbag deployment process, so as to accurately calculate the distance and speed in all directions during the airbag deployment process, and at the same time calculate the real-time area of ​​the airbag; the present application realizes non-contact detection, and no manual operation by the evaluator is required throughout the process, thereby avoiding errors and differences in evaluation results caused by human identification, thereby improving the stability, test efficiency and accuracy of the vehicle's judgment on the dangerous deployment of airbags in collision tests.

[0054] In order to make the technical solution of the present application clearer and easier to understand, a method for determining an airbag deployment rate provided in an embodiment of the present application is introduced below.

[0055] It should be noted that the method can be executed by a terminal. Exemplarily, the terminal can be a foldable mobile phone, a tablet computer, a laptop computer or other device. For ease of understanding, the method is introduced below from the perspective of the terminal.

[0056] like Figure 1 As shown in FIG. 1 , this figure is a flow chart of a method for determining an airbag deployment rate provided in this embodiment, and the method comprises the following steps:

[0057] S100: Decomposing the airbag deployment video into a plurality of first pictures according to a first preset time sequence.

[0058] In this embodiment, optionally, the following steps are further included before step S100:

[0059] S001: Obtain the target video, capture the segment from the start of the airbag popping out to the maximization of the airbag area, and obtain the airbag deployment video; the target video is a continuous video from the first moment to the second moment, the first moment is the moment before the airbag starts to pop out, and the second moment is the moment after the airbag area is maximized.

[0060] Among them, since the airbag deployment speed is too fast, a high-speed camera is generally used to shoot the video of the airbag deployment. Since the airbag deployment process is short, the shooting is extended for a period of time before and after the airbag deployment to obtain a target video; in the present application, it is only necessary to intercept the segment from the beginning of the airbag popping out to the maximization of the airbag area; therefore, in this embodiment, the target video is imported into the analysis software to trim the target video and only retain the segment from the beginning of the airbag popping out to the maximization of the airbag area to obtain the airbag deployment video. The target video is a continuous video from the first moment to the second moment, the first moment being the moment before the airbag starts to pop out, and the second moment is the moment after the airbag area is maximized.

[0061] Specifically, the first preset time is 1ms;

[0062] Specifically, the actual time of the airbag deployment video is generally 200ms. Under normal circumstances, the naked eye cannot see the action occurring in such a short time. After the airbag deployment video is obtained by a high-speed camera, it is converted and played back with a playback time of 20s to play the airbag deployment process with an actual time of 200ms. The video frame rate is obtained based on the ratio of the playback time to the actual time. The video frame rate in this embodiment is 100. Since each picture must be segmented according to the actual time of 1ms, in this embodiment, it is decomposed into 200 first pictures.

[0063] Optionally, when the airbag deployment video is decomposed into a plurality of first images according to a first preset time sequence, the sizes of the first images are the same to ensure the accuracy of the calculated airbag deployment rate per millisecond.

[0064] S200: Calculate a first ratio M according to the circular mark on the dummy's head in the first image; the first ratio is a ratio of the image moving distance to the actual moving distance.

[0065] In this embodiment, optionally, step S200 includes the following steps:

[0066] S201: Identify a circular mark on the dummy's head in any first image to obtain an image diameter of the circular mark;

[0067] S202: according to the diameter of the image marked by the circle and actual diameter , use formula (1) to calculate the first ratio M;

[0068] Formula (I).

[0069] Among them, in the vehicle collision test, when judging whether the airbag is deployed dangerously, a dummy is generally placed in the driving position of the vehicle to be tested for testing, and the dummy's head has a circular mark;

[0070] During the test, the moving distance between two adjacent first images needs to be converted into the actual moving distance to calculate the airbag deployment rate; and during the test, the actual diameter of the circular mark on the dummy's head is fixed. 60mm;

[0071] Therefore, firstly identify the circular mark on the dummy head in any first picture to obtain the image diameter of the circular mark, and then and actual diameter , using the formula , calculate the first ratio to realize the conversion of the image moving distance into the actual moving distance, and the specific implementation method will be described in detail below.

[0072] S300: Processing all first images one by one in chronological order to obtain position information of the airbag contour line of each first image.

[0073] Among them, since the airbag contour line does not unfold in an arc-shaped wave during the airbag deployment process, and the traditional recognition of contour pixel points can only detect the target, but cannot recognize the irregular edge of the object being detected; therefore, in this application, a convolutional neural network and a Torch-YOLO8 architecture are used to jointly establish an image edge detection model, and multiple first images are sequentially input into the image edge detection model, and the image edge detection model performs instance segmentation on the multiple first images to accurately identify the irregular airbag contour line; the input of the image edge detection model is all the first images, and the output of the image edge detection model is the position information of the airbag contour line of each first image; the position information of the airbag contour line is the coordinates of multiple contour points constituting the airbag contour line;

[0074] Specifically, the present application uses a convolutional neural network to perform convolution operations on image data, performs sliding window calculations on the image, and extracts features of the edges of the identified objects through filters (also known as convolution kernels) and pooling layers, and relies on the Torch-YOLO8 architecture to implement instance segmentation to identify the contour of the airbag; based on this, the distance and speed in all directions during the airbag deployment process can be calculated, not limited to the horizontal and vertical directions, and the real-time area of ​​the airbag can be calculated. The detection time window is set to the moment when the airbag reaches the maximum area, and the termination condition of the airbag pop-up calculation is the moment when the airbag area is maximized. The instance segmentation result is integrated into the calculation process as one of the calculation conditions.

[0075] S400: extracting feature points of each first image according to the position information of the airbag contour line of each first image; the feature points include: X-axis extreme value points and Y-axis extreme value points.

[0076] Specifically, in the present application, a coordinate system is established with the position where the airbag begins to pop out as the origin, the X-axis extreme point is the outermost contour point of the airbag contour line in the X-axis direction, and the X-axis direction is perpendicular to the dummy head; the Y-axis extreme point is the outermost contour point of the airbag contour line in the Y-axis direction, and the Y-axis direction is parallel to the dummy head; in the present application, the X-axis direction is the horizontal direction, and the Y-axis direction is the vertical direction.

[0077] S500: Calculating the X-axis airbag deployment rate, the Y-axis airbag deployment rate and the combined deployment rate at each moment within the first preset time according to the X-axis extreme value points, the Y-axis extreme value points and the first ratio of two adjacent first images.

[0078] In this embodiment, optionally, step S500 includes the following steps:

[0079] S501: Subtract the X-axis extreme value points of two adjacent first images to obtain the X-axis image movement distance of the two adjacent first images ;

[0080] S502: Moving distance according to X-axis image And the first ratio M, the actual moving distance of the X-axis within the first preset time is calculated using formula (II) ;

[0081] Formula (II);

[0082] S503: Based on the actual moving distance of the X-axis within the first preset time , use formula (III) to calculate the airbag deployment rate on the X axis ;

[0083] Formula (III);

[0084] in: T is the first preset time;

[0085] S504: Subtract the Y-axis extreme value points of the two adjacent first images to obtain the Y-axis image movement distance of the two adjacent first images ;

[0086] S505: Moving distance according to Y-axis image And the first ratio M, the actual moving distance of the Y axis within the first preset time is calculated using formula (IV) ;

[0087] Formula (IV);

[0088] S506: According to the actual moving distance of the Y axis within the first preset time , use formula (5) to calculate the airbag deployment rate on the Y axis ;

[0089] Formula (V);

[0090] S507: Based on the airbag deployment rate on the X axis and the airbag deployment rate on the Y axis , use formula (VI) to calculate the combined expansion rate ;

[0091] Formula (VI).

[0092] Specifically, after extracting the X-axis extreme value point and the Y-axis extreme value point of the airbag contour line of each first image, the X-axis extreme value points of two adjacent first images are then subtracted in turn to obtain the X-axis image movement distance of the two adjacent first images. ; and move the distance according to the X-axis image And the first ratio M, using the formula Calculate the actual moving distance of the X axis within the first preset time ; and using the formula Calculate the airbag deployment rate on the X axis , where each image is cut at intervals of 1 ms, so in this embodiment, T is 1 ms; at the same time, the Y-axis extreme value points of two adjacent first images are subtracted in turn to obtain the Y-axis image movement distance of the two adjacent first images ; and move the image according to the Y axis distance And the first ratio M, using the formula Calculate the actual moving distance of the Y axis within the first preset time ; and using the formula Calculate the airbag deployment rate on the Y axis Finally, the formula Calculate the combined deployment rate within the first preset time ;

[0093] Specifically, in this embodiment, the convolutional neural network and Torch-YOLO8 architecture are supported on a variety of hardware such as CPU or GPU (Graphics Processing Unit). If the program deployment machine is equipped with a GPU, it can support running all computing tasks on the GPU, greatly accelerating computing efficiency, reducing latency, and increasing image recognition efficiency to milliseconds. In some embodiments, the GPU acceleration option is displayed in the GUI interface. When the user checks the option, the CPU hardware information in the current environment will be automatically read, and all computing tasks will be transferred to the GPU hardware through the task scheduling file to achieve dynamic operating environment configuration.

[0094] In this embodiment, optionally, the following steps are further included after S500:

[0095] S600: Storing and outputting the X-axis airbag deployment rate corresponding to each moment within the first preset time , Y-axis airbag deployment rate and the combined expansion rate .

[0096] Specifically, in some embodiments, the airbag deployment rates of all X axes obtained from the time when the airbag begins to pop out to when the airbag area is maximized are calculated. , Y-axis airbag deployment rate and the combined expansion rate The corresponding data are stored in the airbag deployment rate database shown in Table 1, so as to facilitate subsequent vehicle collision tests and confirm the stability of the vehicle;

[0097] Table 1 Airbag deployment rate database

[0098]

[0099] Since the first preset time is 1ms, and the moving speed of the airbag within 1ms is usually regarded as the instantaneous rate, because 1ms is a very short time interval. On this time scale, it is usually assumed that the speed of the airbag does not change much, so it can be approximately considered that its moving speed within 1ms is equal to the instantaneous speed at this moment; therefore, in the table, R is the shooting time corresponding to the first picture that is arranged later in time among two adjacent first pictures; N is the number of first pictures; in this embodiment: is the shooting time of the first picture, is the airbag deployment rate on the X axis corresponding to the moment when the first picture was taken, is the airbag deployment rate on the Y axis corresponding to the moment when the first picture was taken, is the combined expansion rate corresponding to the moment when the first picture is taken; The shooting time of the second first picture, is the airbag deployment rate on the X axis corresponding to the moment when the second first picture was taken, is the airbag deployment rate on the Y axis corresponding to the moment when the second first picture was taken, is the combined expansion rate corresponding to the moment when the second first picture was taken; is the shooting time of the first picture of the Nth image, is the airbag deployment rate on the X axis corresponding to the moment when the Nth first picture was taken, is the airbag deployment rate on the Y axis corresponding to the moment when the Nth first picture was taken, is the combined expansion rate corresponding to the shooting moment of the Nth first picture; in this embodiment, N is 200.

[0100] Specifically, in some embodiments, the airbag deployment rates of all X axes obtained from the time when the airbag begins to pop out to when the airbag area is maximized are calculated. , Y-axis airbag deployment rate and the combined expansion rate The corresponding generation is as follows Figure 3 The air bag deployment rate curve is shown.

[0101] Combination of the above Figure 1 and Figure 3The airbag deployment rate determination method provided in the embodiment of the present application is introduced in detail. The airbag deployment rate determination system, electronic device and computer-readable storage medium provided in the embodiment of the present application will be introduced in conjunction with the accompanying drawings.

[0102] like Figure 2 As shown, this figure is a schematic diagram of an airbag deployment rate determination system provided by the present application, the system comprising:

[0103] A first processing module 2, the first processing module 2 is used to decompose the airbag deployment video into a plurality of first images according to a first preset time sequence; the sizes of the first images are the same;

[0104] A second processing module 3, the second processing module 3 is used to process all the first images one by one in chronological order to obtain the position information of the airbag contour line of each first image;

[0105] The third processing module 4 is used to calculate the first ratio M according to the circular mark on the dummy's head in the first image; the first ratio is the ratio of the image distance to the actual distance; and according to the position information of the airbag contour line of each first image, extract the feature points of each first image, the feature points include: X-axis extreme point and Y-axis extreme point; according to the X-axis extreme point, Y-axis extreme point and the first ratio of two adjacent first images, respectively calculate the X-axis airbag deployment rate, Y-axis airbag deployment rate and combined deployment rate at each moment within the first preset time.

[0106] In this embodiment, optionally, it further includes:

[0107] A first recognition module 6, the first recognition module 6 is connected to the first processing module 2, and the first recognition module 6 is used to recognize the circular mark of the dummy head in any first picture to obtain the image diameter of the circular mark;

[0108] The first recognition module 6 is connected to the third processing module 4, and the third processing module 4 is also configured to process the image of the circular mark according to the diameter of the circular mark. and actual diameter , use formula (1) to calculate the first ratio M;

[0109] Formula (I).

[0110] In this embodiment, optionally, the third processing module 4 is further configured to:

[0111] Subtract the X-axis extreme value points of the two adjacent first images to obtain the X-axis image movement distance of the two adjacent first images ;

[0112] Move distance according to X-axis image And the first ratio M, the actual moving distance of the X-axis within the first preset time is calculated using formula (II) ;

[0113] Formula (II);

[0114] According to the actual moving distance of the X axis within the first preset time , use formula (III) to calculate the airbag deployment rate on the X axis ;

[0115] Formula (III);

[0116] in: T is the first preset time;

[0117] Subtract the Y-axis extreme value points of the two adjacent first images to obtain the Y-axis image movement distance of the two adjacent first images ;

[0118] Move the image according to the Y axis And the first ratio M, the actual moving distance of the Y axis within the first preset time is calculated using formula (IV) ;

[0119] Formula (IV);

[0120] According to the actual moving distance of the Y axis within the first preset time , use formula (5) to calculate the airbag deployment rate on the Y axis ;

[0121] Formula (V);

[0122] Airbag deployment rate according to the X-axis and the airbag deployment rate on the Y axis , use formula (VI) to calculate the combined expansion rate ;

[0123] Formula (VI).

[0124] In this embodiment, optionally, it further includes:

[0125] The first acquisition module 1 is used to acquire the target video. The first acquisition module 1 is connected to the first processing module 2. The first processing module 2 is also configured to intercept a segment from the start of the airbag popping out to the maximization of the airbag area to obtain an airbag deployment video; the target video is a continuous video from a first moment to a second moment, the first moment is the moment before the airbag starts to pop out, and the second moment is the moment after the airbag area is maximized.

[0126] In this embodiment, optionally, it further includes:

[0127] The first storage module 5 is connected to the third processing module 4, and the first storage module 5 is used to store and output the airbag deployment rate of the X axis corresponding to each moment within the first preset time. , Y-axis airbag deployment rate and the combined expansion rate .

[0128] The airbag deployment rate determination system provided in the embodiment of the present application may correspond to executing the airbag deployment rate determination method described in the embodiment of the present application, and the above functions of each module of the system correspond to implementing Figure 1 For the sake of brevity, the corresponding process of the method shown will not be repeated here.

[0129] An embodiment of the present application also provides an electronic device, 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, the method for determining the airbag deployment rate as described in the above embodiment is implemented.

[0130] like Figure 4 As shown, the computer system of the electronic device includes a CPU 401, which can perform various appropriate actions and processes according to the program stored in the ROM 402 or the program loaded from the storage part 408 to the RAM 403. In the RAM 403, various programs and data required for system operation are also stored. The CPU 401, the ROM 402 and the RAM 403 are connected to each other through a bus 404. The I / O interface 405 is also connected to the bus 404. Among them, the CPU 401 represents a central processing unit, the ROM 402 represents a read-only memory, the RAM 403 represents a random access memory, and the I / O represents input / output.

[0131] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube, a liquid crystal display, etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.

[0132] In particular, the process of the airbag deployment rate determination method described in the above embodiment can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains program code for executing the airbag deployment rate determination method in the above embodiment. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the CPU 401, the above functions defined in the present computer system are executed.

[0133] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for determining the airbag deployment rate as in the above embodiment is implemented.

[0134] Specifically, the computer-readable storage medium may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed by the electronic device, the electronic device implements the airbag deployment rate determination method as described in the above embodiment.

[0135] It should be noted that the computer-readable storage medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above.

[0136] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and its core ideas of this application. The above are only preferred implementation methods of this application. It should be pointed out that due to the limitations of textual expression and the objective existence of infinite specific structures, ordinary technicians in this technical field can make several improvements, modifications or changes without departing from the principles of this application, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the concept and technical solution of the invention to other occasions without improvement, should be regarded as the scope of protection of this application.

Claims

1. A method for determining an airbag deployment rate, characterized in that: The steps include: S100: Decomposing the airbag deployment video into a plurality of first images according to a first preset time sequence; S200: Calculating a first ratio M according to the circular mark on the dummy's head in the first picture; The first ratio is the ratio of the image moving distance to the actual moving distance; S300: Processing all the first images one by one in chronological order to obtain position information of the airbag contour line of each of the first images; S400: extracting feature points of each of the first images according to the position information of the airbag contour line of each of the first images; the feature points include: an X-axis extreme point and a Y-axis extreme point; S500: Calculating the X-axis airbag deployment rate, the Y-axis airbag deployment rate, and the combined deployment rate at each moment in the first preset time, respectively, according to the X-axis extreme value points, the Y-axis extreme value points, and the first ratio of two adjacent first images; Wherein: step S500 includes the following steps: S501: Subtract the X-axis extreme value points of two adjacent first images to obtain the X-axis image movement distance of the two adjacent first images. ; S502: Moving distance according to the X-axis image And the first ratio M, using formula 2 to calculate the actual moving distance of the X axis within the first preset time ; Formula 2: S503: Based on the actual moving distance of the X-axis within the first preset time , use formula 3 to calculate the airbag deployment rate on the X axis ; Formula 3; in: T is the first preset time; S504: Subtract the Y-axis extreme value points of two adjacent first images to obtain the Y-axis image movement distance of the two adjacent first images. ; S505: Moving the image according to the Y-axis distance And the first ratio M, the actual moving distance of the Y axis within the first preset time is calculated using formula 4 ; Formula 4; S506: According to the actual moving distance of the Y axis within the first preset time , use formula 5 to calculate the airbag deployment rate on the Y axis ; Formula 5; S507: Airbag deployment rate according to the X-axis and the airbag deployment rate on the Y axis , the combined expansion rate is calculated using formula 6 ; Formula six.

2. The method for determining the airbag deployment rate according to claim 1, characterized in that: Step S200 includes the following steps: S201: Identify a circular mark on the dummy's head in any of the first images, and obtain an image diameter of the circular mark; S202: according to the image diameter of the circular mark and actual diameter , calculate the first ratio M using formula 1; Formula 1.

3. The method for determining the airbag deployment rate according to claim 1, characterized in that: Before step S100, the following steps are also included: S001: Obtain a target video, capture a segment from the start of the airbag popping out to the point where the airbag area is maximized, and obtain the airbag deployment video; the target video is a continuous video from a first moment to a second moment, the first moment being the moment before the airbag starts to pop out, and the second moment being the moment after the airbag area is maximized.

4. The method for determining the airbag deployment rate according to claim 1, characterized in that: After S500, the following steps are also included: S600: Storing and outputting the airbag deployment rate of the X axis corresponding to each moment within the first preset time , Y-axis airbag deployment rate and the combined expansion rate .

5. The method for determining the airbag deployment rate according to claim 1, characterized in that: When the airbag deployment video is decomposed into a plurality of first images according to a first preset time sequence, the sizes of the first images are the same.

6. An airbag deployment rate determination system, characterized in that: include: A first processing module (2), the first processing module (2) being used to decompose the airbag deployment video into a plurality of first images according to a first preset time sequence; A second processing module (3), the second processing module (3) is used to process all the first images one by one in chronological order to obtain position information of the airbag contour line of each of the first images; A third processing module (4), the third processing module (4) is used to calculate a first ratio M according to the circular mark on the dummy's head in the first picture; The first ratio is a ratio of the image distance to the actual distance; and extracting feature points of each of the first images according to the position information of the airbag contour lines of each of the first images, the feature points including: an X-axis extreme point and a Y-axis extreme point; and calculating the X-axis airbag deployment rate, the Y-axis airbag deployment rate, and the combined deployment rate at each moment in the first preset time according to the X-axis extreme point, the Y-axis extreme point, and the first ratio of two adjacent first images; Wherein: the X-axis extreme value points of two adjacent first images are subtracted to obtain the X-axis image movement distance of the two adjacent first images ; According to the X-axis image movement distance And the first ratio M, using formula 2 to calculate the actual moving distance of the X axis within the first preset time ; Formula 2: According to the actual moving distance of the X-axis within the first preset time , use formula 3 to calculate the airbag deployment rate on the X axis ; Formula 3; in: T is the first preset time; Subtract the Y-axis extreme value points of two adjacent first images to obtain the Y-axis image movement distance of the two adjacent first images. ; According to the Y-axis image movement distance And the first ratio M, the actual moving distance of the Y axis within the first preset time is calculated using formula 4 ; Formula 4; According to the actual moving distance of the Y axis within the first preset time , use formula 5 to calculate the airbag deployment rate on the Y axis ; Formula 5; The airbag deployment rate according to the X-axis and the airbag deployment rate on the Y axis , the combined expansion rate is calculated using formula 6 ; Formula six.

7. An electronic 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 airbag deployment rate determination method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the airbag deployment rate determination method according to any one of claims 1 to 5 is implemented.

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