Head collision prevention alarm method and device, electronic equipment, storage medium and vehicle

Abstract

The invention provides a head collision prevention alarm method and device, electronic equipment, a storage medium and a vehicle. The method comprises the following steps: acquiring an internal image of a vehicle; identifying user information of at least one user in the vehicle interior image to obtain user information of each user; the user information comprises a human body position, a human head position and a user attribute of the user; traversing user information of each user in the vehicle interior image, and determining an alarm scene where the current traversal user is located according to the human body position of the current traversal user; according to the currently traversed head position of the user, judging whether the currently traversed head position of the user falls into an alarm area corresponding to the alarm scene; wherein different alarm scenes correspond to different alarm areas; if the judgment result is yes, outputting alarm information of the current traversal user; the alarm information comprises at least one of the human body position, the human head position or the user attribute of the currently traversed user.

Description

Technical Field

[0001] The present disclosure relates to the field of alarm technology, and in particular to an anti-collision head alarm method, device, electronic device, storage medium, and vehicle. Background Art

[0002] In related alarm technologies, a camera is usually used to capture a target image of a target object; the key point positions of the target object are determined based on the target image, and then the key point positions of the target object are used to generate the action of the target object; the action of the target object is then compared with preset dangerous actions to determine whether the action of the target object is a dangerous action; if the judgment result is yes, an alarm message such as a flashing light alarm or a rapid buzzing alarm is issued.

[0003] However, in related alarm technologies, flashing lights or rapid beeps are issued to all users. Since there are usually multiple users in a vehicle, when these alarm technologies are used in a vehicle, the target users inside the vehicle do not know whether the alarm message is directed at them, and therefore their perception of the alarm message is weak. Summary of the Invention

[0004] The present disclosure provides an anti-head collision alarm method, device, electronic equipment, storage medium and vehicle.

[0005] According to a first aspect of the present disclosure, there is provided an anti-head collision alarm method, comprising:

[0006] Acquire a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image acquired by at least one non-depth image collector disposed in the vehicle cabin;

[0007] Identifying user information of at least one user in the vehicle interior image to obtain user information of each user; wherein the user information includes location information and basic user information of the user; the location information includes a body position and a head position, and the basic user information includes at least one of a user name and a user attribute;

[0008] Traversing the position information of each user in the vehicle interior image, and determining the alarm scene of the currently traversed user according to the body position of the currently traversed user;

[0009] According to the currently traversed head position of the user, determining whether the currently traversed head position of the user falls into the alarm area corresponding to the alarm scene; wherein different alarm scenes correspond to different alarm areas;

[0010] If the judgment result is yes, the alarm information of the user currently traversed is output; the alarm information includes the basic user information of the user currently traversed.

[0011] In one embodiment, identifying user information of at least one user in the vehicle interior image to obtain user information of each user includes:

[0012] Identifying basic user information of each user in the vehicle interior image to obtain basic user information of each user;

[0013] Identify the body and head of each user in the vehicle interior image, and obtain a body circumference frame of each user and a head circumference frame of each head in the vehicle interior image;

[0014] Determine an intersection-and-union (IoU) ratio between each of the human body bounding boxes and each of the head bounding boxes, and match the user corresponding to the human body bounding box with the head bounding box whose IoU ratio is not less than a preset IoU threshold;

[0015] The center point position of the human body circumference frame of the user is determined as the human body position of the user, and the center point position of the head circumference frame of the head matching the user is determined as the head position of the user.

[0016] In one embodiment, if the judgment result is yes, outputting the alarm information of the currently traversed user includes:

[0017] If the judgment result is yes, determining the original alarm probability; the original alarm probability is the alarm probability determined according to the alarm scene currently traversed by the user;

[0018] The original alarm probability is corrected using a preset alarm sensitivity coefficient corresponding to the alarm area to obtain a target alarm probability corresponding to the alarm area; the preset alarm sensitivity coefficient is used to indicate the triggering difficulty corresponding to the alarm scenario currently traversed by the user;

[0019] In response to the target alarm probability being greater than a preset alarm probability threshold, the alarm information of the currently traversed user is output.

[0020] In one embodiment, before determining whether the currently traversed head position of the user falls into the alarm area corresponding to the alarm scene based on the currently traversed head position of the user, the anti-head collision alarm method includes:

[0021] receiving an alarm area adjustment instruction for adjusting an alarm area corresponding to an alarm scene currently traversed by the user;

[0022] The size of the alarm area is scaled according to the alarm area scaling factor in the alarm area adjustment instruction.

[0023] In one embodiment, before determining the alarm scene in which the currently traversed user is located based on the currently traversed user's body position, the anti-head collision alarm method includes:

[0024] An output instruction for outputting the alarm information is received.

[0025] In one embodiment, the vehicle interior image includes a first vehicle interior image acquired by a non-depth image collector disposed in front of a front seat; the alarm scene includes a front seat alarm scene;

[0026] Accordingly,

[0027] If the judgment result is yes, determining the original alarm probability includes:

[0028] Obtaining the head area of ​​the user currently traversing in the first vehicle interior image;

[0029] Determining a first initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a first preset head area threshold;

[0030] Comparing the user's head area with a standard head area to obtain a relative head area;

[0031] determining a first alarm probability correction value based on a comparison between the relative head area and a preset relative head area threshold;

[0032] The first initial alarm probability is corrected using the first alarm probability correction value to obtain an original alarm probability.

[0033] In one embodiment, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector disposed in front of the front seat and a second vehicle interior image captured by a non-depth image collector disposed behind an obstacle; the alarm scene includes a second-row seat alarm scene;

[0034] Accordingly,

[0035] If the judgment result is yes, determining the original alarm probability includes:

[0036] Obtaining the head area of ​​the user currently traversing in the first vehicle interior image;

[0037] Determining a second initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a second preset head area threshold;

[0038] determining a second alarm probability correction value based on whether there is a human head matching the currently traversed user in the second vehicle interior image;

[0039] The second initial alarm probability is corrected using the second alarm probability correction value to obtain an original alarm probability.

[0040] In one embodiment, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector disposed in front of a front seat and a second vehicle interior image captured by a non-depth image collector disposed behind an obstacle; the alarm scene includes an alarm scene in an aisle area;

[0041] Accordingly,

[0042] If the judgment result is yes, determining the original alarm probability includes:

[0043] Obtaining the head area of ​​the user currently traversing in the first vehicle interior image;

[0044] determining a third initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a third preset head area threshold;

[0045] determining a third alarm probability correction value according to whether there is a human head matching the currently traversed user in the second vehicle interior image;

[0046] The third initial alarm probability is corrected using the third alarm probability correction value to obtain an original alarm probability.

[0047] In one embodiment, the vehicle interior image includes a second vehicle interior image acquired by a non-depth image collector disposed behind the obstacle; the alarm scene includes an alarm scene in the area under the aisle;

[0048] Accordingly,

[0049] If the judgment result is yes, determining the original alarm probability includes:

[0050] Obtaining the head area of ​​the user currently traversing in the second vehicle interior image;

[0051] determining a fourth initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a fourth preset head area threshold;

[0052] Obtaining a grayscale value of each pixel in the second vehicle interior image;

[0053] Comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of first target pixel points whose grayscale value is greater than the preset grayscale value;

[0054] Determining a fourth alarm probability correction value based on a comparison between the number of the first target pixel points and the first preset number of pixel points;

[0055] The fourth initial alarm probability is corrected using the fourth alarm probability correction value to obtain an original alarm probability.

[0056] In one embodiment, the vehicle interior image includes a second vehicle interior image acquired by a non-depth image collector disposed behind an obstacle; the alarm scene includes a door alarm scene;

[0057] Accordingly,

[0058] If the judgment result is yes, determining the original alarm probability includes:

[0059] Obtaining a grayscale value of each pixel in the second vehicle interior image;

[0060] Comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of second target pixel points whose grayscale value is smaller than the preset grayscale value;

[0061] Determining whether the number of the second target pixel points is less than the second preset number of pixel points;

[0062] If the judgment result is yes, obtaining the head confidence of the user currently traversing in the second vehicle interior image;

[0063] Determining whether the head confidence is not less than a preset head confidence threshold;

[0064] If the judgment result is yes, obtaining the head area of ​​the user currently traversing in the second vehicle interior image;

[0065] determining whether an area of ​​a head of the user currently traversing in the second vehicle interior image is not less than a fifth preset head area threshold;

[0066] If the judgment result is yes, the original alarm probability is determined to be the preset alarm probability.

[0067] According to a second aspect of the present disclosure, there is provided an anti-head collision alarm device, comprising:

[0068] An acquisition unit, configured to acquire a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image acquired by at least one non-depth image acquirer disposed in the vehicle cabin;

[0069] an identification unit, configured to identify user information of at least one user in the vehicle interior image, and obtain user information of each user; wherein the user information includes location information and basic user information of the user; the location information includes a body position and a head position, and the basic user information includes at least one of a user name and a user attribute;

[0070] a determining unit, configured to traverse the position information of each user in the vehicle interior image, and determine an alarm scene in which the currently traversed user is located based on the body position of the currently traversed user;

[0071] a judgment unit, configured to judge, based on the currently traversed head position of the user, whether the currently traversed head position of the user falls into an alarm area corresponding to the alarm scenario; wherein different alarm scenarios correspond to different alarm areas;

[0072] The output unit is configured to output the alarm information of the user currently traversed if the judgment result is yes; the alarm information includes the basic user information of the user currently traversed.

[0073] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0074] at least one processor; and

[0075] a memory communicatively connected to at least one processor; wherein,

[0076] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of the first aspect.

[0077] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute the method of the aforementioned first aspect.

[0078] According to a fifth aspect of the present disclosure, a vehicle is provided, comprising the anti-collision head alarm device provided by the second aspect of the present disclosure or the electronic device provided by the third aspect of the present disclosure.

[0079] The present disclosure provides a head collision prevention alarm method, device, electronic device, storage medium, and vehicle. The method provided by the present disclosure includes: acquiring a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image captured by at least one non-depth image collector set in the vehicle cabin; identifying user information of at least one user in the vehicle interior image to obtain user information of each user; wherein the user information includes the user's location information and user basic information; the location information includes the body position and the head position, and the user basic information includes at least one of the user's name and user attributes; traversing the location information of each user in the vehicle interior image, and determining the alarm scene of the currently traversed user based on the body position of the currently traversed user; based on the head position of the currently traversed user, determining whether the head position of the currently traversed user falls within the alarm area corresponding to the alarm scene; wherein different alarm scenes correspond to different alarm areas; if the judgment result is yes, outputting the alarm information of the currently traversed user; the alarm information includes at least one of the body position, the head position, or the user attribute of the currently traversed user.

[0080] According to the solution disclosed herein, by identifying user information in the vehicle interior image, the user's location information and basic user information can be obtained; the location information includes the body position and head position, and the basic user information includes at least one of the user's name and user attributes. Furthermore, based on the user's body position, the alarm scenario in which the user is located can be determined. When the user's head position falls within the alarm area corresponding to the alarm scenario, an alarm message containing the user's basic information can be output. Because the alarm message includes at least one of the user's name and user attributes, compared to flashing light alarms or rapid beeping alarms in related technologies, users at risk of head collision can accurately perceive that the alarm message is directed at them, improving their awareness of the alarm message.

[0081] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0083] Figure 1 A schematic diagram of the seat distribution structure of a vehicle cabin provided by an embodiment of the present disclosure;

[0084] Figure 2 A flowchart of the anti-head collision alarm method provided by an embodiment of the present disclosure;

[0085] Figure 3 A schematic diagram of the structure of key points of the human body provided by an embodiment of the present disclosure;

[0086] Figure 4 A flowchart of a method for determining a user's name provided in an embodiment of the present disclosure;

[0087] Figure 5 A flowchart of the first method for obtaining the original alarm probability provided by an embodiment of the present disclosure;

[0088] Figure 6 A flowchart of a second method for obtaining an original alarm probability provided by an embodiment of the present disclosure;

[0089] Figure 7 A flowchart of a third method for obtaining an original alarm probability provided by an embodiment of the present disclosure;

[0090] Figure 8 A flowchart of a fourth method for obtaining an original alarm probability provided by an embodiment of the present disclosure;

[0091] Figure 9 A flowchart of the fifth method for obtaining the original alarm probability provided by an embodiment of the present disclosure;

[0092] Figure 10 A schematic structural diagram of the anti-head collision alarm device provided by an embodiment of the present disclosure;

[0093] Figure 11 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0094] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0095] An anti-collision head alarm method provided in an embodiment of the present disclosure can be applied to vehicles equipped with a non-depth image collector, such as an infrared (IR) camera. Its execution entity can be a processor on the vehicle side or in the cloud, such as the processor of the vehicle's anti-collision head alarm module, or the vehicle's entire vehicle controller.

[0096] In one embodiment, the seats in the vehicle cabin are arranged as follows: Figure 1As shown, the seats in the vehicle cabin include the front, second, and third rows of seats; the second and third rows of seats are collectively referred to as the rear seats. The front row refers to seats 0 and 1, the second row refers to seats 2 and 3, the third row refers to seats 4 and 5, and the aisle area refers to seat 7. The entertainment screen is typically located between the front and second rows of seats and is usually located on the roof of the cabin.

[0097] In one embodiment, the aisle area can be divided into an upper aisle area and a lower aisle area.

[0098] In one embodiment, the IR camera inside the vehicle can be arranged in front of the front seat, such as in front of or behind the rearview mirror in the vehicle. The IR camera arranged in front of the front seat is used to collect front row video or front row image.

[0099] In one embodiment, the IR camera inside the vehicle may also be set behind the entertainment screen, for example, twenty centimeters behind the entertainment screen; the IR camera set behind the entertainment screen is used to collect rear video or rear images of the second row of seats, third row of seats and aisle area inside the cabin.

[0100] In one embodiment, the number of cameras located in front of the front seats can be one or more. Since a single camera can capture complete front-row video or images, the number of cameras located in front of the front seats is preferably one. This disclosure does not limit the number of cameras. Similarly, the number of cameras located behind the entertainment screen is preferably one.

[0101] In one embodiment, IR cameras may also be provided in front of the front seats and behind the entertainment screen.

[0102] In one embodiment, since the seats in the cabin are divided into the front row, the second row, and the third row, and obstacles such as the entertainment screen are typically located between the front and second rows, at the top of the cabin, users in the front row who lean back or users in the second row who lean forward may collide with the entertainment screen. However, if users in the third row lean forward, they are too far away from the entertainment screen and therefore do not face the risk of collision. Only when exiting the third row, they may move toward the door near the second row, at which point there is a risk of collision with the entertainment screen. Furthermore, users in the aisle may be in the upper aisle area, which can only be captured by the non-depth image collector located in front of the front row, or in the lower aisle area, which can only be captured by the non-depth image collector located behind the obstacle. Regardless of whether the user is in the upper aisle area or the lower aisle area, there is a risk of collision with the entertainment screen.

[0103] Based on this, according to the user's body position in the vehicle, the scenarios in which the user may hit his head in the vehicle can generally be divided into front seat alarm scenarios, second row seat alarm scenarios, upper aisle area alarm scenarios, lower aisle area alarm scenarios and door alarm scenarios; correspondingly, the risk areas where the user's head hits the entertainment screen generally include the alarm area corresponding to the front seat alarm scenario, the alarm area corresponding to the second row seat alarm scenario, the alarm area corresponding to the upper aisle area alarm scenario, the alarm area corresponding to the lower aisle area alarm scenario and the alarm area corresponding to the door alarm scenario.

[0104] like Figure 2 As shown, the anti-head collision alarm method provided by the embodiment of the present disclosure includes the following steps:

[0105] Step 201, obtaining an image of the interior of a vehicle;

[0106] In one embodiment, the vehicle interior image refers to a vehicle interior image captured by at least one non-depth image collector disposed in a vehicle cabin;

[0107] In one embodiment, the non-depth image collector can be arranged in front of the front seats, such as in front of or behind the rearview mirror. The non-depth image collector arranged in front of the front seats is used to collect the first vehicle interior image of the front seats, the second row of seats and the aisle area in the cabin.

[0108] In one embodiment, the non-depth image collector may also be set behind an obstacle, such as an entertainment screen, for example, twenty centimeters behind the entertainment screen; the non-depth image collector set behind the entertainment screen is used to collect a second vehicle interior image of the second row of seats, the third row of seats and the area under the aisle inside the cabin.

[0109] Based on this, in one embodiment, step 201 includes:

[0110] Acquire a first vehicle interior image and / or a second vehicle interior image; the first vehicle interior image refers to a vehicle interior image acquired by a non-depth image collector disposed in front of the front seat, and the second vehicle interior image refers to a vehicle interior image acquired by a non-depth image collector disposed behind an obstacle;

[0111] Step 202: Identify user information of at least one user in the vehicle interior image and obtain user information of each user; wherein the user information includes location information and basic user information of the user; the location information includes body position and head position, and the basic user information includes at least one of a user name and user attributes;

[0112] In one embodiment, a human body detection network and a human body key point recognition network may be used to identify human bodies and heads in the vehicle interior image, and then the identified human bodies and heads are matched to obtain the human body position and head position of each user; specifically:

[0113] A human body detection network may be used to identify the human body of each user in the vehicle interior image.

[0114] In one embodiment, the human detection network typically consists of a backbone network, a shoulder network, and a head network, and is used to detect the presence of users in the vehicle interior image and output the coordinates of the bounding box corresponding to each user. For example, the coordinates of the upper left vertex and the lower right vertex of the bounding box are provided.

[0115] In one embodiment, the human body detection network can also output the confidence of the human body bounding box corresponding to each user. Based on this, before outputting the coordinates of the human body bounding box corresponding to each user, the human body bounding box whose confidence is less than the preset human body bounding box confidence must be deleted from the human body bounding box output by the human body detection network.

[0116] In one embodiment, after obtaining the coordinates of the human body external bounding box, an image of each selected position of the human body external bounding box may be cropped from the vehicle interior image to obtain at least one user image; then, a human body key point recognition network is used to recognize each user image to obtain the coordinates of the human body key points of each user image;

[0117] In one embodiment, if Figure 3 As shown in , the key points of the human body refer to the points that can represent the key positions of the human body. Figure 3 Points 1 to 24 in the figure. Points 1 to 4 represent the key points of the head.

[0118] Determine the circumscribed frame corresponding to the head key point among the human body key points of each user image as the head circumscribed frame, and obtain at least one head circumscribed frame.

[0119] Determine the intersection-and-union ratio of the human body external bounding box and the head external bounding box, and determine the human body corresponding to the human body external bounding box and the head corresponding to the head external bounding box whose intersection-and-union ratio is greater than a preset intersection-and-union ratio threshold as the human body and head of the same user; in this way, the human body and head bound to each user are obtained.

[0120] Since the body position is usually the center point of the body bounding box, and the head position is usually the center point of the head bounding box, the body position and head position of the user can be bound for the user.

[0121] In one embodiment, the intersection-over-union (IoU) of the human body's circumference frame and the head's circumference frame can reflect the degree of overlap between the human body's circumference frame and the head's circumference frame; therefore, a human body and head with an IoU greater than a preset IoU threshold are usually the human body and head of the same user.

[0122] In one embodiment, the intersection-and-union ratio between a human body circumference frame and each head circumference frame can be determined, and the human body and head corresponding to the human body circumference frame and the head circumference frame whose intersection-and-union ratio is greater than a preset intersection-and-union ratio are determined to be the human body and head of the same user.

[0123] In one embodiment, if the vehicle interior image is captured by a non-depth image collector disposed in front of a front seat, identifying user information of at least one user in the vehicle interior image includes:

[0124] User information of at least one user in the first vehicle interior image is identified.

[0125] In one embodiment, if the vehicle interior image is captured by a non-depth image collector disposed behind an entertainment screen, identifying user information of at least one user in the vehicle interior image includes:

[0126] User information of at least one user in the second vehicle interior image is identified.

[0127] In one embodiment, if non-depth image collectors are provided in front of the front seats and behind the entertainment screen, identifying user information of at least one user in the vehicle interior image includes:

[0128] User information of at least one user in the first vehicle interior image and the second vehicle interior image is identified.

[0129] In one embodiment, a face recognition network can be used to identify the face of each user in the vehicle interior image to obtain the user name of each user; then, the user basic information matching the user name is searched from the user basic information database; in this way, the user's body position, head position and user basic information can be bound.

[0130] In one embodiment, the user basic information includes at least one of the user name or user attributes; the user attributes include at least one of the user age characteristic and the gender characteristic; the user age characteristic is used to indicate whether the user is an adult or a child; the user gender characteristic is used to indicate whether the user is male or female.

[0131] In one embodiment, the user name of each user may also be obtained by recognizing the voice in the vehicle;

[0132] Specifically, using a sound recognition network to recognize the sound in the vehicle, and obtaining the voiceprint characteristics and sound source location corresponding to the sound;

[0133] Determining the user name corresponding to the voiceprint feature using a mapping relationship between the voiceprint feature and the user name;

[0134] Determine the distance between the position coordinates of the sound source position and the position coordinates of the human body position;

[0135] If the distance is less than a preset distance value, the name of the user corresponding to the human body position is determined to be the user name.

[0136] Step 203, traversing the position information of each user in the vehicle interior image, and determining the alarm scene of the currently traversed user according to the body position of the currently traversed user;

[0137] In one embodiment, the user's body external bounding box that is currently traversed can be obtained first, and then the center point position of the body external bounding box can be used as the user's body position; then, the area where the user is located can be determined based on the position coordinates of the center point position of the user's body external bounding box that is currently traversed.

[0138] In one embodiment, the waist key point or the hip key point among the currently traversed user's body key points may also be used as the user's body position. Figure 3 At least one of points 15 to 18.

[0139] In one embodiment, as described above, based on the user's body position in the vehicle, the alarm scenarios in which the user in the vehicle may hit his head can generally be divided into front seat alarm scenarios, second row seat alarm scenarios, upper aisle area alarm scenarios, lower aisle area alarm scenarios and door alarm scenarios.

[0140] In one embodiment, if the currently traversed user is located in the front seat, then the alarm scene in which the user is located is determined to be the front seat alarm scene;

[0141] In one embodiment, if the currently traversed user is located in the second row of seats, it is determined that the alarm scene in which the user is located is the second row of seats alarm scene;

[0142] In one embodiment, if the currently traversed user is located in the upper aisle area, it is determined that the alarm scene in which the user is located is the upper aisle area alarm scene;

[0143] In one embodiment, if the currently traversed user is located in the upper aisle area, it is determined that the alarm scene in which the user is located is the lower aisle area alarm scene;

[0144] In one embodiment, if the currently traversed user is located at a car door, it is determined that the alarm scene in which the user is located is a car door alarm scene.

[0145] Step 204: judging whether the currently traversed head position of the user falls within the alarm area corresponding to the alarm scenario based on the currently traversed head position of the user;

[0146] In one embodiment, corresponding to the alarm scenarios, different alarm scenarios correspond to different alarm areas.

[0147] In one embodiment, the external bounding box of the head of the currently traversed user can be obtained first, and then the center point position of the external bounding box of the head can be used as the head position of the currently traversed user; then, based on the position coordinates of the center point position of the external bounding box of the head of the currently traversed user, it is determined whether the head position of the currently traversed user falls into the alarm area corresponding to the alarm scene.

[0148] In one embodiment, corresponding to the alarm scenario, the risk areas where the user's head collides with the entertainment screen generally include the alarm area corresponding to the front seat alarm scenario, the alarm area corresponding to the second row seat alarm scenario, the alarm area corresponding to the aisle area alarm scenario, the alarm area corresponding to the lower aisle area alarm scenario, and the alarm area corresponding to the door alarm scenario.

[0149] Specifically, in one embodiment,

[0150] If the alarm scene currently traversed by the user is the front seat alarm scene, then judging whether the head position of the currently traversed user falls into the alarm area corresponding to the front seat alarm scene according to the head position of the currently traversed user;

[0151] If the alarm scene currently traversed by the user is the second-row seat alarm scene, then judging whether the head position of the currently traversed user falls into the alarm area corresponding to the second-row seat alarm scene according to the head position of the currently traversed user;

[0152] If the alarm scene currently traversed by the user is the aisle area alarm scene, then judging whether the head position of the currently traversed user falls into the alarm area corresponding to the aisle area alarm scene according to the head position of the currently traversed user;

[0153] If the alarm scene currently traversed by the user is the aisle area alarm scene, then judging whether the head position of the currently traversed user falls into the alarm area corresponding to the aisle area alarm scene according to the head position of the currently traversed user;

[0154] If the alarm scene currently traversed by the user is a car door alarm scene, it is determined based on the head position of the currently traversed user whether the head position of the currently traversed user falls into the alarm area corresponding to the car door alarm scene.

[0155] In one embodiment, before step 204 , the anti-head collision alarm provided by the present disclosure may further include: obtaining an alarm area corresponding to the alarm scene.

[0156] In one embodiment, the alarm area corresponding to the alarm scene includes:

[0157] Acquire a plurality of training images, wherein the training images are images of a human head at a boundary position of the alarm area;

[0158] In one embodiment, the boundaries of the alarm area are typically defined by a product manager.

[0159] In one embodiment, taking the front seat alarm scenario as an example, a product manager can designate a person to sit in the front seat to calibrate the alarm area. The person can sit in both front seats, or just one of them, and lean back to the edge of the alarm area. A non-depth image collector located in front of the front seat captures training images.

[0160] Recognize the human heads in the training image to obtain a plurality of human head bounding boxes in the training image; wherein one human head corresponds to one human head bounding box;

[0161] Determine the center point position of each of the head circumference frames to obtain the center point positions of multiple head circumference frames;

[0162] In one embodiment, the center point position is used to indicate the center coordinate point of the circumscribed frame of the head.

[0163] In one embodiment, the center point position of the head circumference frame may be obtained through the coordinates of the head circumference frame.

[0164] A closed area formed by connecting lines of multiple center points is determined as an alarm area.

[0165] In one embodiment, the size of the warning area refers to the size of the area enclosed by all head positions at the boundary positions of the warning area in all training images.

[0166] Step 205: If the judgment result is yes, output the alarm information of the user currently traversed; the alarm information includes the basic user information of the user.

[0167] In one embodiment, if the judgment result is yes, it means that the user is at risk of hitting the entertainment screen with his head, and an alarm should be issued.

[0168] In one embodiment, the alarm information may be a text alarm information displayed on the entertainment screen and / or the central control screen, or may be a voice alarm information.

[0169] In one embodiment, the content of the text alarm message or the voice alarm message may be “Little Ming in the front seat, be careful not to bump your head.”

[0170] In one embodiment, the alarm information may further include an alarm scenario.

[0171] In one embodiment, an alarm message may be output each time a user is traversed; the basic user information of the traversed users may also be cached until all users are traversed, and then the basic user information of the users who are at risk of colliding their heads with the entertainment screen is uniformly output.

[0172] In one embodiment, after outputting an alarm message, the alarm can be turned off and then turned on again after a preset duration. The preset duration can be 10 seconds or other durations, and is not limited in this disclosure. Turning off the alarm after outputting an alarm message not only allows users to perceive the alarm message but also saves computing resources.

[0173] The anti-head collision alarm method provided by the present disclosure includes: acquiring a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image collected by at least one non-depth image collector set in the vehicle cabin; identifying user information of at least one user in the vehicle interior image, and obtaining user information of each of the users; wherein the user information includes the user's body position, head position and user attributes; traversing the user information of each user in the vehicle interior image, and determining the alarm scene in which the currently traversed user is located based on the body position of the currently traversed user; judging whether the currently traversed user's head position falls into the alarm area corresponding to the alarm scene based on the currently traversed user's head position; wherein different alarm scenes correspond to different alarm areas; if the judgment result is yes, outputting the alarm information of the currently traversed user; the alarm information includes at least one of the currently traversed user's body position, head position or user attributes.

[0174] According to the disclosed solution, by identifying user information in the vehicle interior image, the user's body position, head position, and user attributes can be obtained. Furthermore, based on the user's body position, the alarm scenario the user is in can be determined. When the user's head position falls within the alarm area corresponding to the alarm scenario, an alarm message containing the user information can be output. This improves the user's awareness of alarm information.

[0175] In one embodiment, if Figure 4As shown, step 202 includes:

[0176] Step 401: identifying basic user information of each user in the vehicle interior image to obtain basic user information of each user;

[0177] In one embodiment, a trained face recognition network may be used to recognize the face of each user in the vehicle interior image to obtain the user name of each user.

[0178] In one embodiment, the training set of the face recognition network may include a large number of facial features, each labeled with a user name. The facial features may include the facial features of users who frequently use a vehicle. For example, for a family vehicle, the facial features collected may include the facial features of all family members; for a company vehicle, the facial features collected may include the facial features of all company employees.

[0179] In one embodiment, searching a user basic information database for user basic information that matches the user name;

[0180] In one embodiment, the basic user information includes at least one of the user name or user attributes; the user attributes include the user's age characteristics and gender characteristics, etc.; the user's age characteristics are used to indicate whether the user is an adult or a child; the user's gender characteristics are used to indicate whether the user is male or female.

[0181] In one embodiment, the user's age characteristics and gender characteristics can be pre-bound to the user's name and stored in the vehicle or cloud to form a basic user information database.

[0182] In one embodiment, a user attribute recognition network based on graph matching or torso length may be directly used to identify the user's age characteristics.

[0183] Step 402 , identifying the body and head of each user in the vehicle interior image, and obtaining a body bounding box of each user and a head bounding box of each head in the vehicle interior image;

[0184] Step 403: Determine the intersection-and-union (IoU) of each of the human body bounding boxes and each of the head bounding boxes, and match the user corresponding to the human body bounding box with the head bounding box whose IoU is not less than a preset IoU threshold.

[0185] In one embodiment, the intersection-over-union (IoU) of the human body's circumference frame and the head's circumference frame can reflect the degree of overlap between the human body's circumference frame and the head's circumference frame; therefore, a human body and head with an IoU greater than a preset IoU threshold are usually the human body and head of the same user.

[0186] In one embodiment, the intersection-and-union ratio between a human body circumference frame and each head circumference frame can be determined, and the human body and head corresponding to the human body circumference frame and the head circumference frame whose intersection-and-union ratio is greater than a preset intersection-and-union ratio are determined to be the human body and head of the same user.

[0187] Step 404 : determining the center point position of the body circumference frame of the user as the body position of the user, and determining the center point position of the head circumference frame of the head matching the user as the head position of the user.

[0188] In one embodiment, step 205 includes:

[0189] If the judgment result is yes, determining the original alarm probability; the original alarm probability is the alarm probability determined according to the alarm scene currently traversed by the user;

[0190] In one embodiment, if the judgment result is yes, it means that the head position of the user currently traversing falls into the alarm area corresponding to the alarm scene.

[0191] In one embodiment, if the alarm scenario described for the currently traversed user's head position is a front seat alarm scenario, then if the judgment result is yes, it means that the currently traversed user's head position falls into the alarm area corresponding to the front seat alarm scenario.

[0192] In one embodiment, if the alarm scenario described for the currently traversed user's head position is a two-row seat alarm scenario, then if the judgment result is yes, it means that the currently traversed user's head position falls into the alarm area corresponding to the two-row seat alarm scenario.

[0193] In one embodiment, if the alarm scenario described for the currently traversed user's head position is an aisle area alarm scenario, then if the judgment result is yes, it means that the currently traversed user's head position falls into the alarm area corresponding to the aisle area alarm scenario.

[0194] In one embodiment, if the alarm scene described by the currently traversed user's head position is an alarm scene for the area under the aisle, then if the judgment result is yes, it means that the currently traversed user's head position falls into the alarm area corresponding to the alarm scene for the area under the aisle.

[0195] In one embodiment, if the alarm scene described by the currently traversed user's head position is a car door alarm scene, then if the judgment result is yes, it means that the currently traversed user's head position falls into the alarm area corresponding to the car door alarm scene.

[0196] Correcting the original alarm probability using the preset alarm sensitivity coefficient corresponding to the alarm area to obtain a target alarm probability corresponding to the alarm area;

[0197] In one embodiment, the preset alarm sensitivity coefficient is used to indicate the triggering difficulty corresponding to the alarm scenario currently traversed by the user;

[0198] In one embodiment, the preset alarm sensitivity coefficient can be set by the user; for example, through the human-computer interaction interface on the central control screen.

[0199] In one embodiment, taking the alarm scenario of the front seat alarm scenario as an example:

[0200] If the user often leans back from the front seat to talk with the user in the back seat, and at the same time does not expect the vehicle to send out alarm messages all the time, the preset alarm sensitivity coefficient corresponding to the front seat alarm can be set to a value between 0 and 1, such as 0.5, which will reduce the number of alarms corresponding to the front seat alarm scenario to a certain extent.

[0201] In one embodiment, if the user does not want to issue an alarm message, the preset alarm sensitivity coefficient of the corresponding alarm scenario can be set to 0.

[0202] In response to the target alarm probability being greater than a preset alarm probability threshold, outputting alarm information for the user.

[0203] In one embodiment, before step 202, the anti-head collision alarm method includes:

[0204] receiving an alarm area adjustment instruction for adjusting an alarm area corresponding to an alarm scene currently traversed by the user;

[0205] In one embodiment, the alarm area adjustment instruction is issued by the user.

[0206] In one embodiment, the user's alarm area adjustment instruction may be received via the vehicle's central control screen.

[0207] In one embodiment, a voice alarm area adjustment instruction issued by the user may also be received via a microphone.

[0208] The size of the alarm area is scaled according to the alarm area scaling factor in the alarm area adjustment instruction.

[0209] In one embodiment, the alarm area corresponding to different alarm scenarios may be increased or decreased according to the user's expectation of the alarm sensitivity for different alarm scenarios.

[0210] In one embodiment, the alarm area scaling factor may be 150%, indicating that the alarm area is adjusted to 1.5 times the current alarm area; the alarm area scaling factor may also be 50%, indicating that the alarm area is adjusted to half the current alarm area; this is not limited in the present disclosure.

[0211] In one embodiment, outputting the alarm information of the currently traversed user includes:

[0212] If no closing instruction for closing the output of the alarm information corresponding to the alarm scene of the currently traversed user is received, the alarm information of the currently traversed user is output.

[0213] In one embodiment, the shutdown instruction is issued by a user.

[0214] In one embodiment, the user's shutdown command may be received via the vehicle's central control screen.

[0215] In one embodiment, a voice shutdown command issued by the user may also be received via a microphone.

[0216] In one embodiment, the closing instruction issued by the user may also be received via a mechanical button.

[0217] In one embodiment, in addition to the closing instruction, an opening instruction may also be received.

[0218] In one embodiment, the alarm information corresponding to the alarm scenario may be output or not output according to the user's alarm expectation for different alarm scenarios.

[0219] In one embodiment, if the user in the front seat often leans back to talk with the user in the second seat, in order not to affect the conversation experience, a shutdown command may be issued and the alarm message may not be output.

[0220] In one embodiment, taking the front seat scenario as an example, the user's body is located in the front seat, and their head is located in the alarm area corresponding to the front seat scenario. Therefore, to trigger an alarm for the front seat alarm scenario, it is sufficient to obtain a first vehicle interior image captured by a non-depth image collector located in front of the front seat.

[0221] Based on this, the vehicle interior image includes a first vehicle interior image acquired by a non-depth image collector arranged in front of the front seat. The alarm scene includes a front seat alarm scene;

[0222] Correspondingly, such as Figure 5 As shown, if the judgment result is yes, determining the original alarm probability includes:

[0223] Step 501: Obtain the head area of ​​the user currently traversing in the first vehicle interior image;

[0224] In one embodiment, the length and width of the head bounding box of the currently traversed user's head may be multiplied to obtain the head area of ​​the currently traversed user;

[0225] In one embodiment, the human head circumference frame is generally rectangular.

[0226] In one embodiment, since the image captured by the non-depth image collector is a planar image, the closer the human head is to the camera, the larger its area on the first vehicle interior image; conversely, the farther the human head is from the camera, the smaller its area on the first vehicle interior image.

[0227] Step 502: determining a first initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a first preset head area threshold;

[0228] In one embodiment, only when the head position of the currently traversed user is within the alarm area corresponding to the front seat alarm scene, the user of the currently traversed user is at risk of colliding with the entertainment screen, and the first initial alarm probability is 1 at this time; when the head position of the currently traversed user is not within the first target area, the head of the currently traversed user is not at risk of colliding with the entertainment screen, and the first initial alarm probability is 0 at this time.

[0229] In one embodiment, because the first vehicle interior image is not captured by the depth image collector, the size of the user's head is highly correlated with the distance between the user's head and the obstacle. Specifically, the larger the user's head size, the smaller the distance between the user's head and the front-row image collector, and the larger the distance between the user's head and the obstacle. Conversely, the smaller the user's head size, the larger the distance between the user's head and the front-row image collector, and the smaller the distance between the user's head and the obstacle.

[0230] In one embodiment, the first preset head area threshold refers to the area value of the corresponding head circumscribed frame on the first vehicle interior image when the head is at the boundary of the alarm area corresponding to the front seat scene.

[0231] In one embodiment, the first preset head area threshold may also refer to the area value of the head circumscribed frame corresponding to the first vehicle interior image when the head contacts an obstacle.

[0232] In one embodiment, the area value of the external bounding box of the human head corresponding to the boundary of the alarm area corresponding to the front seat scene, and the area value of the external bounding box of the human head corresponding to the first vehicle interior image when the human head contacts an obstacle can also be used simultaneously to jointly determine the original alarm probability.

[0233] Step 503: Compare the user's head area with a standard head area to obtain a relative head area;

[0234] In one embodiment, the standard head area refers to the area value of the corresponding head external frame on the first vehicle interior image when the user sits in the front seat in a standard sitting posture (without stretching the head forward or backward).

[0235] In one embodiment, multiple first vehicle interior images of a user sitting in a standard sitting posture in the front seat may be collected, and then the area value of the external bounding box of the head in each first vehicle interior image may be calculated. Finally, the area values ​​of the multiple external bounding boxes of the head may be averaged to obtain the standard head area.

[0236] In one embodiment, the relative head area refers to the degree to which the user's head area is scaled relative to the standard head area. Therefore, the relative head area is highly correlated with the distance between the user's head and the head corresponding to the standard sitting posture, that is, the distance between the user's head and the obstacle.

[0237] Step 504: determining a first alarm probability correction value based on a comparison between the relative head area and a preset relative head area threshold;

[0238] In one embodiment, the larger the relative head area is, the lower the degree of scaling of the user's head area is, that is, the closer the distance between the head and the head corresponding to the standard sitting posture is; when the relative head area is 1, it indicates that the sitting posture of the user in the front seat is the standard sitting posture, and there is no situation of stretching the head backward; when the relative head area is less than 1, and the smaller the relative head area is, the greater the distance the head of the user in the front seat stretches backward; at this time, the alarm probability should be increased.

[0239] Step 505: Use the first alarm probability correction value to correct the first initial alarm probability to obtain an original alarm probability.

[0240] In one embodiment, taking the second-row seat alarm scenario as an example, the user's body is located in the second row of seats, and their head is located within the alarm area corresponding to the second-row seat alarm scenario. When the user in the second row seat leans forward, the first vehicle interior image is captured by the non-depth image collector located in front of the front seat. Therefore, both the second-row seat body information and the alarm area corresponding to the second-row seat alarm scenario are captured. However, if the user in the second row seat leans forward too far, the non-depth image collector located behind the obstacle will not be able to capture the user's head information. In this case, the alarm probability must be increased.

[0241] Therefore, to accurately alarm the second-row seat alarm scenario, it is necessary to obtain a first vehicle interior image captured by a non-depth image collector set in front of the front seat, and a second vehicle interior image captured by a non-depth image collector set behind the obstacle;

[0242] Based on this, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector arranged in front of the front seats and a second vehicle interior image captured by a non-depth image collector arranged behind the obstacle; the alarm scene includes a second-row seat alarm scene.

[0243] Correspondingly, such as Figure 6 As shown, if the judgment result is yes, determining the original alarm probability includes:

[0244] Step 601: Obtain the head area of ​​the user currently traversing in the first vehicle interior image;

[0245] In one embodiment, the currently traversed user refers to a user whose body position is in the second row of seats and whose head position is in the alarm area corresponding to the second row of seats alarm scenario.

[0246] In one embodiment, since the first vehicle interior image is captured by a non-depth image collector arranged in front of the front row of seats, both human body information of the second row of seats and alarm area information corresponding to the alarm scene of the second row of seats can be obtained.

[0247] Step 602: Determine a second initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a second preset head area threshold;

[0248] In one embodiment, the second preset head area threshold refers to the area value of the corresponding head circumscribed frame on the first vehicle interior image when the head is at the boundary of the second-row seat alarm scene.

[0249] In one embodiment, the second preset head area threshold may also refer to the area value of the head circumscribed frame corresponding to the first vehicle interior image when the head contacts an obstacle.

[0250] In one embodiment, the area value of the external bounding box of the human head corresponding to the first vehicle interior image when the human head is at the boundary of the second row of seats alarm scene and the area value of the external bounding box of the human head corresponding to the first vehicle interior image when the human head contacts an obstacle can also be used simultaneously to jointly determine the second initial alarm probability.

[0251] In one embodiment, when the area of ​​the user's head is smaller than the area of ​​the second preset head external frame, it means that the head is close to the non-depth image collector set in front of the front seat and is also close to the obstacle, and the possibility of a head collision is greater. Therefore, the corresponding second initial alarm probability is also greater.

[0252] Step 603: determining a second alarm probability correction value based on whether a head matching the currently traversed user exists in the second vehicle interior image;

[0253] In one embodiment, when the head of a user in the second row of seats extends too far forward, the non-depth image collector set behind the obstacle cannot collect the user's head information. In this case, the second initial alarm probability must be increased.

[0254] In one embodiment, when there is no head matching the currently traversed user in the second vehicle interior image, it means that when the head of the user in the second row of seats extends forward too far, the non-depth image collector set behind the obstacle cannot collect the user's head information. At this time, the second initial alarm probability must be increased.

[0255] In one embodiment, when a human head matching the currently traversed user exists in the second vehicle interior image, it means that when the head of the user in the second row of seats is not extended forward far enough, the non-depth image collector set behind the obstacle can collect the user's head information. At this time, the second initial alarm probability can be reduced.

[0256] Step 604: Use the second alarm probability correction value to correct the second initial alarm probability to obtain an original alarm probability.

[0257] In one embodiment, taking the aisle area alarm scenario as an example, the user's body is located in the aisle area, and their head is located in the alarm area corresponding to the aisle area alarm scenario. When the user in the aisle area extends their head forward, the first vehicle interior image is captured by the non-depth image collector located in front of the front seat. Therefore, both the body information in the aisle area and the alarm area information corresponding to the aisle area alarm scenario can be acquired. However, if the user in the aisle area extends their head forward too far, the non-depth image collector located behind the obstacle will not be able to capture the user's head information. In this case, the alarm probability must be increased.

[0258] Therefore, to accurately alarm the aisle area alarm scene, it is necessary to obtain a first vehicle interior image captured by a non-depth image collector set in front of the front seat, and a second vehicle interior image captured by a non-depth image collector set behind the obstacle;

[0259] Based on this, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector arranged in front of the front seat and a second vehicle interior image captured by a non-depth image collector arranged behind the obstacle; the alarm scene includes an alarm scene in the aisle area.

[0260] Correspondingly, such as Figure 7 As shown, if the judgment result is yes, determining the original alarm probability includes:

[0261] Step 701: Obtain the head area of ​​the user currently traversing in the first vehicle interior image;

[0262] In one embodiment, the currently traversed user refers to a user whose body position is in the aisle area and whose head position is in the alarm area corresponding to the alarm scenario of the aisle area.

[0263] In one embodiment, since the first vehicle interior image is captured by a non-depth image collector arranged in front of the front seats, it is possible to obtain both human body information in the aisle area and alarm area information corresponding to the alarm scene in the aisle area.

[0264] Step 702: Determine a third initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a third preset head area threshold;

[0265] In one embodiment, the third preset head area threshold refers to the area value of the corresponding human head circumscribed frame on the first vehicle interior image when the human head is at the boundary of the regional alarm scene in the aisle.

[0266] In one embodiment, the third preset head area threshold may also refer to the area value of the head circumscribed frame corresponding to the first vehicle interior image when the head contacts an obstacle.

[0267] In one embodiment, the area value of the external bounding box of the human head corresponding to the boundary of the regional alarm scene in the aisle and the area value of the external bounding box of the human head corresponding to the interior image of the first vehicle when the human head contacts an obstacle can also be used simultaneously to jointly determine the third initial alarm probability.

[0268] In one embodiment, when the area of ​​the user's head is smaller than the area of ​​the third preset head external frame, it means that the user's head is close to the non-depth image collector set in front of the front seat and is also close to the obstacle, and the possibility of a head collision is greater. Therefore, the corresponding third initial alarm probability is also greater.

[0269] Step 703: determining a third alarm probability correction value based on whether a head matching the currently traversed user exists in the second vehicle interior image;

[0270] In one embodiment, when the user's head in the aisle area extends too far forward, the non-depth image collector set behind the obstacle cannot collect the user's head information. In this case, the third initial alarm probability must be increased.

[0271] In one embodiment, when there is no human head matching the currently traversed user in the second vehicle interior image, it means that when the user's head in the aisle area extends forward too far, the non-depth image collector set behind the obstacle cannot collect the user's head information. At this time, the third initial alarm probability must be increased.

[0272] In one embodiment, when a human head matching the currently traversed user exists in the second vehicle interior image, it indicates that when the user's head in the aisle area does not extend forward far enough, the non-depth image collector behind the obstacle can collect the user's head information. At this time, the third initial alarm probability can be reduced.

[0273] Step 704: Use the third alarm probability correction value to correct the third initial alarm probability to obtain an original alarm probability.

[0274] In one embodiment, taking the aisle area alarm scenario as an example, a user's body is located in the aisle area, and their head is located in the alarm zone corresponding to the aisle area alarm scenario. When the user in the aisle area leans forward, the second vehicle interior image is captured by a non-depth image collector positioned behind the obstacle. Therefore, both the user's body information in the aisle area and the alarm zone information corresponding to the aisle area alarm scenario are captured.

[0275] Therefore, to accurately alarm the alarm scene in the area under the aisle, it is only necessary to obtain the second vehicle interior image captured by the non-depth image collector set behind the obstacle;

[0276] Based on this, the vehicle interior image includes a second vehicle interior image captured by a non-depth image collector arranged behind the obstacle; and the alarm scene includes an alarm scene in the area under the aisle.

[0277] Correspondingly, such as Figure 8 As shown, if the judgment result is yes, determining the original alarm probability according to the alarm probability determination method corresponding to the alarm area includes:

[0278] Step 801: Obtain the head area of ​​the user currently traversing in the second vehicle interior image;

[0279] In one embodiment, the currently traversed user refers to a user whose body position is in the area below the aisle and whose head position is in the alarm area corresponding to the alarm scenario of the area below the aisle.

[0280] In one embodiment, since the second vehicle interior image is collected by a non-depth image collector arranged behind the obstacle, it is possible to obtain both human body information in the area under the aisle and alarm area information corresponding to the alarm scene in the area under the aisle.

[0281] Step 802: Determine a fourth initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a fourth preset head area threshold;

[0282] In one embodiment, the fourth preset head area threshold refers to the area value of the corresponding human head circumscribed frame on the second vehicle interior image when the human head is at the boundary of the alarm scene in the area below the aisle.

[0283] In one embodiment, the fourth preset head area threshold may also refer to the area value of the head circumscribed frame corresponding to the second vehicle interior image when the head contacts an obstacle.

[0284] In one embodiment, the fourth initial alarm probability can be determined simultaneously by using the area value of the external bounding box of the human head corresponding to the second vehicle interior image when the human head is at the boundary of the alarm scene in the area below the aisle, and the area value of the external bounding box of the human head corresponding to the second vehicle interior image when the human head contacts an obstacle.

[0285] In one embodiment, when the area of ​​the user's head is smaller than the area of ​​the fourth preset head external frame, it means that the head is close to the non-depth image collector set behind the obstacle and is also close to the obstacle, and the possibility of a head collision is greater. Therefore, the corresponding fourth initial alarm probability is also greater.

[0286] Step 803: Obtain the grayscale value of each pixel in the second vehicle interior image;

[0287] In one embodiment, when a user's head is extended too far forward in the aisle area, it can easily block the non-depth image collector behind the obstacle, causing the grayscale values ​​of pixels in the second vehicle interior image to decrease. High levels of occlusion indicate that the user's head is very close to the obstacle, necessitating an increase in the fourth initial alarm probability.

[0288] Step 804, comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of first target pixels whose grayscale value is greater than the preset grayscale value;

[0289] In one embodiment, the number of first target pixel points whose grayscale values ​​are greater than the preset grayscale value is used to indicate the degree of occlusion of the second vehicle interior image.

[0290] In one embodiment, the preset grayscale value is a grayscale value that is relatively dark, such as a grayscale value below 120. A grayscale value of 0 represents black.

[0291] Step 805: determining a fourth alarm probability correction value based on a comparison between the number of the first target pixels and the first preset number of pixels;

[0292] Step 806: Use the fourth alarm probability correction value to correct the fourth initial alarm probability to obtain an original alarm probability.

[0293] In one embodiment, taking a car door alarm scenario as an example, the user's body is positioned near the car door, and their head is within the alarm zone corresponding to the car door alarm scenario. When the user makes a move, the second vehicle interior image is captured by a non-depth image collector positioned behind the obstacle. This allows the user to capture both the body information near the car door and the alarm zone corresponding to the car door alarm scenario.

[0294] Therefore, to accurately alarm the regional alarm scene in the aisle, it is only necessary to obtain the second vehicle interior image captured by the non-depth image collector set behind the obstacle;

[0295] Based on this, the vehicle interior image includes a second vehicle interior image captured by a non-depth image collector arranged behind the obstacle; and the alarm scene includes a door alarm scene.

[0296] Correspondingly, such as Figure 9 As shown, if the judgment result is yes, determining the original alarm probability includes:

[0297] Step 901: Obtain the grayscale value of each pixel in the second vehicle interior image;

[0298] In one embodiment, the grayscale value of a pixel in the second vehicle interior image is used to indicate the degree to which a non-depth image collector disposed behind an obstacle is blocked.

[0299] Step 902, comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of second target pixels whose grayscale value is smaller than the preset grayscale value;

[0300] In one embodiment, a greater number of second target pixel points whose grayscale values ​​are less than the preset grayscale value indicates a lower luminous flux of the second vehicle interior image, and a higher degree of occlusion of the non-depth image collector disposed behind the obstacle.

[0301] Step 903: determine whether the number of the second target pixel points is less than the second preset number of pixel points;

[0302] Step 904: If the judgment result is yes, obtaining the head confidence of the user currently traversing in the second vehicle interior image;

[0303] In one embodiment, the number of the second target pixel points is less than the second preset pixel point number, indicating that the non-depth image collector set behind the obstacle is not highly blocked, and further judgment can be made.

[0304] In one embodiment, the number of the second target pixels is not less than the second preset number of pixels, indicating that the non-depth image collector disposed behind the obstacle is highly blocked, and the original alarm probability is determined to be 0.

[0305] Step 905: determining whether the head confidence is not less than a preset head confidence threshold;

[0306] In one embodiment, the head confidence is used to indicate the credibility of the corresponding head.

[0307] Step 906: If the judgment result is yes, obtain the head area of ​​the user currently traversing in the second vehicle interior image;

[0308] Step 907: Determine whether the head area of ​​the user currently traversing in the second vehicle interior image is not less than a fifth preset head area threshold;

[0309] In one embodiment, the fifth preset head area threshold refers to the area value of the corresponding head circumscribed frame on the second vehicle interior image when the human body is located at the vehicle door and the human head contacts an obstacle.

[0310] Step 908: If the judgment result is yes, determine the original alarm probability as the preset alarm probability.

[0311] Figure 10 A schematic diagram of the structure of an anti-collision head alarm device provided in an embodiment of the present disclosure is shown in FIG. Figure 10 As shown, the anti-head collision alarm device 1000 includes:

[0312] An acquisition unit 1001 is configured to acquire a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image acquired by at least one non-depth image acquirer disposed within the vehicle cabin;

[0313] an identification unit 1002 configured to identify user information of at least one user in the vehicle interior image and obtain user information of each user; wherein the user information includes location information and basic user information of the user; the location information includes a body position and a head position; and the basic user information includes at least one of a user name and a user attribute;

[0314] The determining unit 1003 is configured to traverse the position information of each user in the vehicle interior image, and determine the alarm scene in which the currently traversed user is located based on the body position of the currently traversed user;

[0315] The judging unit 1004 is configured to judge, based on the currently traversed head position of the user, whether the currently traversed head position of the user falls within the alarm area corresponding to the alarm scenario; wherein different alarm scenarios correspond to different alarm areas;

[0316] The output unit 1005 is configured to output the alarm information of the currently traversed user if the judgment result is yes; the alarm information includes the basic user information of the currently traversed user.

[0317] In one embodiment, the identification unit 1002 is specifically configured to:

[0318] Identifying basic user information of each user in the vehicle interior image to obtain basic user information of each user;

[0319] Identify the body and head of each user in the vehicle interior image, and obtain a body circumference frame of each user and a head circumference frame of each head in the vehicle interior image;

[0320] Determine an intersection-and-union (IoU) ratio between each of the human body bounding boxes and each of the head bounding boxes, and match the user corresponding to the human body bounding box with the head bounding box whose IoU ratio is not less than a preset IoU threshold;

[0321] The center point position of the human body circumference frame of the user is determined as the human body position of the user, and the center point position of the head circumference frame of the head matching the user is determined as the head position of the user.

[0322] In one embodiment, the output unit 1005 is specifically configured to:

[0323] If the judgment result is yes, determining the original alarm probability; the original alarm probability is the alarm probability determined according to the alarm scene currently traversed by the user;

[0324] The original alarm probability is corrected using a preset alarm sensitivity coefficient corresponding to the alarm area to obtain a target alarm probability corresponding to the alarm area; the preset alarm sensitivity coefficient is used to indicate the triggering difficulty corresponding to the alarm scenario currently traversed by the user;

[0325] In response to the target alarm probability being greater than a preset alarm probability threshold, the alarm information of the currently traversed user is output.

[0326] In one embodiment, the anti-head collision alarm device 1000 further includes an alarm area adjustment unit, which is configured to:

[0327] receiving an alarm area adjustment instruction for adjusting an alarm area corresponding to an alarm scene currently traversed by the user;

[0328] The size of the alarm area is scaled according to the alarm area scaling factor in the alarm area adjustment instruction.

[0329] In one embodiment, the determining unit 1003 is specifically configured to:

[0330] If no closing instruction for closing the output of the alarm information corresponding to the alarm scene of the currently traversed user is received, the alarm information of the currently traversed user is output.

[0331] In one embodiment, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector disposed in front of a front seat; and the alarm scene includes a front seat alarm scene.

[0332] Accordingly, the output unit 1005 is specifically configured to:

[0333] Obtaining the head area of ​​the user currently traversing in the first vehicle interior image;

[0334] Determining a first initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a first preset head area threshold;

[0335] Comparing the user's head area with a standard head area to obtain a relative head area;

[0336] determining a first alarm probability correction value based on a comparison between the relative head area and a preset relative head area threshold;

[0337] The first initial alarm probability is corrected using the first alarm probability correction value to obtain an original alarm probability.

[0338] In one embodiment, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector arranged in front of the front seats and a second vehicle interior image captured by a non-depth image collector arranged behind an obstacle; the alarm scene includes a second-row seat alarm scene.

[0339] Accordingly, the output unit 1005 is specifically configured to:

[0340] Obtaining the head area of ​​the user currently traversing in the first vehicle interior image;

[0341] Determining a second initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a second preset head area threshold;

[0342] determining a second alarm probability correction value based on whether there is a human head matching the currently traversed user in the second vehicle interior image;

[0343] The second initial alarm probability is corrected using the second alarm probability correction value to obtain an original alarm probability.

[0344] In one embodiment, the vehicle interior image includes a first vehicle interior image captured by a non-depth image collector arranged in front of the front seats and a second vehicle interior image captured by a non-depth image collector arranged behind an obstacle; the alarm scene includes an alarm scene in the aisle area.

[0345] Accordingly, the output unit 1005 is specifically configured to:

[0346] Obtaining the head area of ​​the user currently traversing in the first vehicle interior image;

[0347] determining a third initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a third preset head area threshold;

[0348] determining a third alarm probability correction value according to whether there is a human head matching the currently traversed user in the second vehicle interior image;

[0349] The third initial alarm probability is corrected using the third alarm probability correction value to obtain an original alarm probability.

[0350] In one embodiment, the vehicle interior image includes a second vehicle interior image captured by a non-depth image collector disposed behind an obstacle; and the alarm scene includes an alarm scene in an area under the aisle.

[0351] Accordingly, the output unit 1005 is specifically configured to:

[0352] Obtaining the head area of ​​the user currently traversing in the second vehicle interior image;

[0353] determining a fourth initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a fourth preset head area threshold;

[0354] Obtaining a grayscale value of each pixel in the second vehicle interior image;

[0355] Comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of first target pixel points whose grayscale value is greater than the preset grayscale value;

[0356] Determining a fourth alarm probability correction value based on a comparison between the number of the first target pixel points and the first preset number of pixel points;

[0357] The fourth initial alarm probability is corrected using the fourth alarm probability correction value to obtain an original alarm probability.

[0358] In one embodiment, the vehicle interior image includes a second vehicle interior image captured by a non-depth image collector disposed behind an obstacle; and the alarm scene includes a door alarm scene.

[0359] Accordingly, the output unit 1005 is specifically configured to:

[0360] Obtaining a grayscale value of each pixel in the second vehicle interior image;

[0361] Comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of second target pixel points whose grayscale value is smaller than the preset grayscale value;

[0362] Determining whether the number of the second target pixel points is less than the second preset number of pixel points;

[0363] If the judgment result is yes, obtaining the head confidence of the user currently traversing in the second vehicle interior image;

[0364] Determining whether the head confidence is not less than a preset head confidence threshold;

[0365] If the judgment result is yes, obtaining the head area of ​​the user currently traversing in the second vehicle interior image;

[0366] determining whether an area of ​​a head of the user currently traversing in the second vehicle interior image is not less than a fifth preset head area threshold;

[0367] If the judgment result is yes, the original alarm probability is determined to be the preset alarm probability.

[0368] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principles are the same, which is not limited in this embodiment.

[0369] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a non-transitory computer-readable storage medium storing computer instructions, and a vehicle.

[0370] Specifically, an embodiment of the present disclosure provides an electronic device, including:

[0371] at least one processor; and

[0372] a memory communicatively connected to at least one processor; wherein,

[0373] The memory stores instructions that can be executed by at least one processor. The instructions are executed by the at least one processor so that the at least one processor can perform the steps of the aforementioned anti-collision head alarm method.

[0374] An embodiment of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the steps of the aforementioned anti-collision head alarm method.

[0375] An embodiment of the present disclosure provides a vehicle, wherein the vehicle includes the aforementioned anti-collision head alarm device or the aforementioned electronic device.

[0376] Figure 11 A schematic block diagram of an example electronic device 1100 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, in-vehicle devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0377] like Figure 11 As shown, the electronic device 1100 includes a computing unit 1101, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 1102 or a computer program loaded from a storage unit 1108 into a RAM (Random Access Memory) 1103. Various programs and data required for the operation of the device 1100 can also be stored in the RAM 1103. The computing unit 1101, the ROM 1102, and the RAM 1103 are connected to each other via a bus 1104. An I / O (Input / Output) interface 1105 is also connected to the bus 1104.

[0378] Various components in device 1100 are connected to an I / O interface 1105, including an input unit 1104, such as a keyboard and mouse; an output unit 1107, such as various types of displays and speakers; a storage unit 1108, such as a magnetic disk and optical disk; and a communication unit 1109, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1109 allows device 1100 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0379] The computing unit 1101 can be various general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of the computing unit 1101 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), various specialized AI (Artificial Intelligence) computing chips, various computing units that run machine learning model algorithms, a DSP (Digital Signal Processor), and any suitable processor, controller, microcontroller, etc. The computing unit 1101 performs the various methods and processes described above, such as the head collision prevention alarm method. For example, in some embodiments, the head collision prevention alarm method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 1108. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 1100 via the ROM 1102 and / or the communication unit 1109. When the computer program is loaded into the RAM 1103 and executed by the computing unit 1101, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the computing unit 1101 may be configured to execute the aforementioned anti-head collision alarm method in any other appropriate manner (for example, by means of firmware).

[0380] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System on Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0381] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0382] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0383] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0384] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A head collision prevention alarm method, characterized in that: include: Acquire a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image acquired by at least one non-depth image collector disposed in the vehicle cabin; Identifying user information of at least one user in the vehicle interior image to obtain user information of each user; wherein the user information includes location information and basic user information of the user; the location information includes a body position and a head position, and the basic user information includes at least one of a user name and a user attribute; Traversing the position information of each user in the vehicle interior image, and determining the alarm scene of the currently traversed user according to the body position of the currently traversed user; According to the currently traversed head position of the user, determining whether the currently traversed head position of the user falls into the alarm area corresponding to the alarm scene; wherein different alarm scenes correspond to different alarm areas; If the judgment result is yes, the alarm information of the user currently traversed is output; the alarm information includes the basic user information of the user currently traversed.

2. The method according to claim 1, characterized in that The identifying user information of at least one user in the vehicle interior image to obtain user information of each user includes: Identifying basic user information of each user in the vehicle interior image to obtain basic user information of each user; Identify the body and head of each user in the vehicle interior image, and obtain a body circumference frame of each user and a head circumference frame of each head in the vehicle interior image; Determine an intersection-and-union (IoU) ratio between each of the human body bounding boxes and each of the head bounding boxes, and match the user corresponding to the human body bounding box with the head bounding box whose IoU ratio is not less than a preset IoU threshold; The center point position of the human body circumference frame of the user is determined as the human body position of the user, and the center point position of the head circumference frame of the head matching the user is determined as the head position of the user.

3. The method according to claim 1, characterized in that If the judgment result is yes, outputting the alarm information of the currently traversed user includes: If the judgment result is yes, determining the original alarm probability; the original alarm probability is the alarm probability determined according to the alarm scene currently traversed by the user; The original alarm probability is corrected using a preset alarm sensitivity coefficient corresponding to the alarm area to obtain a target alarm probability corresponding to the alarm area; the preset alarm sensitivity coefficient is used to indicate the triggering difficulty corresponding to the alarm scenario currently traversed by the user; In response to the target alarm probability being greater than a preset alarm probability threshold, the alarm information of the currently traversed user is output.

4. The method according to claim 1, wherein The method of determining whether the currently traversed head position of the user falls within the alarm area corresponding to the alarm scene according to the currently traversed head position of the user includes: receiving an alarm area adjustment instruction for adjusting an alarm area corresponding to an alarm scene currently traversed by the user; The size of the alarm area is scaled according to the alarm area scaling factor in the alarm area adjustment instruction.

5. The method according to claim 1, wherein The outputting of the alarm information of the currently traversed user includes: If no closing instruction for closing the output of the alarm information corresponding to the alarm scene of the currently traversed user is received, the alarm information of the currently traversed user is output.

6. The method according to claim 3, characterized in that The vehicle interior image includes a first vehicle interior image acquired by a non-depth image collector arranged in front of the front seat; the alarm scene includes a front seat alarm scene; If the judgment result is yes, determining the original alarm probability includes: Obtaining the head area of ​​the user currently traversing in the first vehicle interior image; Determining a first initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a first preset head area threshold; Comparing the user's head area with a standard head area to obtain a relative head area; determining a first alarm probability correction value based on a comparison between the relative head area and a preset relative head area threshold; The first initial alarm probability is corrected using the first alarm probability correction value to obtain an original alarm probability.

7. The method according to claim 3, characterized in that The vehicle interior image includes a first vehicle interior image acquired by a non-depth image collector arranged in front of the front seat and a second vehicle interior image acquired by a non-depth image collector arranged behind the obstacle; the alarm scene includes a second-row seat alarm scene; If the judgment result is yes, determining the original alarm probability includes: Obtaining the head area of ​​the user currently traversing in the first vehicle interior image; Determining a second initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a second preset head area threshold; determining a second alarm probability correction value based on whether there is a human head matching the currently traversed user in the second vehicle interior image; The second initial alarm probability is corrected using the second alarm probability correction value to obtain an original alarm probability.

8. The method according to claim 3, characterized in that The vehicle interior image includes a first vehicle interior image acquired by a non-depth image collector arranged in front of the front seat and a second vehicle interior image acquired by a non-depth image collector arranged behind the obstacle; the alarm scene includes an alarm scene in the aisle area; If the judgment result is yes, determining the original alarm probability includes: Obtaining the head area of ​​the user currently traversing in the first vehicle interior image; determining a third initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a third preset head area threshold; determining a third alarm probability correction value according to whether there is a human head matching the currently traversed user in the second vehicle interior image; The third initial alarm probability is corrected using the third alarm probability correction value to obtain an original alarm probability.

9. The method according to claim 3, characterized in that The vehicle interior image includes a second vehicle interior image acquired by a non-depth image collector disposed behind the obstacle; the alarm scene includes an alarm scene in the area under the aisle; If the judgment result is yes, determining the original alarm probability includes: Obtaining the head area of ​​the user currently traversing in the second vehicle interior image; determining a fourth initial alarm probability based on a comparison between the head area of ​​the currently traversed user and a fourth preset head area threshold; Obtaining a grayscale value of each pixel in the second vehicle interior image; Comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of first target pixel points whose grayscale value is greater than the preset grayscale value; Determining a fourth alarm probability correction value based on a comparison between the number of the first target pixel points and the first preset number of pixel points; The fourth initial alarm probability is corrected using the fourth alarm probability correction value to obtain an original alarm probability.

10. The method according to claim 3, characterized in that The vehicle interior image includes a second vehicle interior image acquired by a non-depth image collector disposed behind an obstacle; the alarm scene includes a vehicle door alarm scene; If the judgment result is yes, determining the original alarm probability includes: Obtaining a grayscale value of each pixel in the second vehicle interior image; Comparing the grayscale value of each pixel with a preset grayscale value, and determining the number of second target pixel points whose grayscale value is smaller than the preset grayscale value; Determining whether the number of the second target pixel points is less than the second preset number of pixel points; If the judgment result is yes, obtaining the head confidence of the user currently traversing in the second vehicle interior image; Determining whether the head confidence is not less than a preset head confidence threshold; If the judgment result is yes, obtaining the head area of ​​the user currently traversing in the second vehicle interior image; determining whether an area of ​​a head of the user currently traversing in the second vehicle interior image is not less than a fifth preset head area threshold; If the judgment result is yes, the original alarm probability is determined to be the preset alarm probability. 11.An anti-head collision alarm device, characterized in that: include: An acquisition unit, configured to acquire a vehicle interior image; wherein the vehicle interior image refers to a vehicle interior image acquired by at least one non-depth image acquirer disposed in the vehicle cabin; an identification unit, configured to identify user information of at least one user in the vehicle interior image, and obtain user information of each user; wherein the user information includes location information and basic user information of the user; the location information includes a body position and a head position, and the basic user information includes at least one of a user name and a user attribute; a determining unit, configured to traverse the position information of each user in the vehicle interior image, and determine an alarm scene in which the currently traversed user is located based on the body position of the currently traversed user; a judgment unit, configured to judge, based on the currently traversed head position of the user, whether the currently traversed head position of the user falls into an alarm area corresponding to the alarm scenario; wherein different alarm scenarios correspond to different alarm areas; The output unit is used to output the alarm information of the user currently traversed if the judgment result is yes; the alarm information includes at least one of the body position, head position or user attribute of the user currently traversed.

12. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 10.

13. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 10.

14. A vehicle, characterized in that: It includes the anti-head collision alarm device according to claim 11 or the electronic device according to claim 12.

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