Method and device for sending information to an emergency call center for a vehicle

Abstract

The present disclosure relates to a method and device, an electronic device and a storage medium for a vehicle to send information to an emergency call center. The method includes: in response to an emergency call being triggered, acquiring image information of an occupant in the cabin; based on the image information, detecting bleeding of the occupant in the cabin; and in response to detecting the bleeding, sending the bleeding to an emergency call center.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method and device, an electronic device and a storage medium for a vehicle to send information to an emergency call center. Background Art

[0002] During road transportation, cars may get into traffic accidents. At this time, if rescue personnel can obtain accident information in time and carry out rescue, the parties involved in the accident can receive timely rescue, thereby reducing property losses and casualties.

[0003] In order to enable rescuers to obtain accident information in a timely manner, an on-board emergency call (eCall) system can be integrated into the car. The eCall system is a typical application of the Internet of Vehicles. Based on automotive sensors, mobile communications, satellite positioning and other technologies, it can contact the public rescue center as soon as the accident occurs, and automatically send the vehicle location and vehicle information to the rescue center. After the rescue center confirms the accident, it will rescue the accident victims.

[0004] However, the traditional emergency call function is difficult to determine the injuries of the occupants in the accident after the accident occurs, and the emergency call cannot confirm the injuries of the people in the car. Summary of the invention

[0005] The present disclosure proposes a technical solution for information sending.

[0006] According to one aspect of the present disclosure, a method for a vehicle to send information to an emergency call center is provided, comprising:

[0007] In response to an emergency call being triggered, acquiring image information of the occupants in the cabin;

[0008] Based on the image information, detecting bleeding of the occupants in the cabin;

[0009] In response to detecting the bleeding condition, the bleeding condition is transmitted to an emergency call center.

[0010] In a possible implementation, the detecting bleeding of the occupant in the cabin based on the image information includes:

[0011] Performing face detection and / or body detection on the image information to determine the occupants in the cabin;

[0012] A blood test is performed on the face and / or body of the occupant to determine the bleeding condition of the occupant in the cabin.

[0013] In a possible implementation, the detecting bleeding of the occupant in the cabin based on the image information includes:

[0014] Based on the blood color information and the blood flow shape information, it is detected based on the image information whether the occupant is bleeding.

[0015] In a possible implementation, the detecting bleeding of the occupant in the cabin based on the image information includes:

[0016] Based on the image information, detecting a body surface area of ​​an occupant in the cabin;

[0017] Dividing the body surface area of ​​the occupant into a plurality of detection areas;

[0018] Detecting blood information in each of the detection areas to obtain a regional detection result of each of the detection areas;

[0019] Based on the regional detection results of each of the detection areas, the bleeding condition of the occupant is determined.

[0020] In a possible implementation, the detecting the body surface area of ​​the occupant in the cabin based on the image information includes:

[0021] Detecting a facial surface area of ​​an occupant in the cabin based on the image information;

[0022] The dividing the body surface area of ​​the occupant into a plurality of detection areas comprises:

[0023] The facial surface area of ​​the occupant is divided into a plurality of detection areas.

[0024] In a possible implementation, detecting blood information in each of the detection areas to obtain a regional detection result of each of the detection areas includes:

[0025] Determining a first confidence level of the presence of bleeding in each detection area based on the shape and area of ​​the blood flow in each detection area;

[0026] Determine whether there is a connected blood flow between adjacent detection areas;

[0027] In response to determining that a first detection area in the detection areas has a connected blood flow with an adjacent second detection area, raising the confidence levels of the plurality of first detection areas and the second detection area to a second confidence level;

[0028] The determining the bleeding condition of the occupant based on the regional detection results of each of the detection areas includes:

[0029] When the first confidence level or the second confidence level exceeds a confidence level threshold, determining that the occupant is bleeding;

[0030] The severity of bleeding is determined based on the area of ​​blood flow in each detection region, and the severity of bleeding is positively correlated with the sum of the areas of blood flow in each detection region.

[0031] In a possible implementation, the detecting bleeding of the occupant in the cabin based on the image information includes:

[0032] In response to detecting bleeding of the occupant in the cabin based on the image information, determining a bleeding body part and a direction of blood flow;

[0033] Based on the bleeding body part and the direction of blood flow, the body part where the starting end of the blood flow is located is used as the bleeding part.

[0034] In a possible implementation, the method further includes:

[0035] Determining the body posture of the occupant in the cabin according to the image information;

[0036] When the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds a set duration, it is determined that the body posture of the cabin occupant is an abnormal body posture.

[0037] In a possible implementation, the method further includes:

[0038] When it is determined that the body posture of the cabin occupant is a preset fracture posture, it is determined that the cabin occupant has a fracture.

[0039] In a possible implementation, the method further includes:

[0040] Determine the vital sign index of the occupant based on the image information, where the vital sign index includes at least one of the following:

[0041] Respiratory rate, blood pressure, heart rate;

[0042] The vital sign indicator is sent to an emergency call center.

[0043] In a possible implementation, the method further includes:

[0044] Determining the severity level of the injury of the occupant in the cabin based on at least one of the determined bleeding condition, abnormal body posture, and vital sign indicators of the occupant;

[0045] The injury severity level is transmitted to an emergency call center.

[0046] According to one aspect of the present disclosure, there is provided a device for a vehicle to send information to an emergency call center, comprising:

[0047] An image information acquisition unit, configured to acquire image information of passengers in the cabin in response to an emergency call being triggered;

[0048] a bleeding condition detection unit, used to detect the bleeding condition of the occupant in the cabin based on the image information;

[0049] The bleeding situation sending unit is used for sending the bleeding situation to an emergency call center in response to detecting the bleeding situation.

[0050] In a possible implementation, the bleeding detection unit includes:

[0051] An occupant detection subunit, configured to perform face detection and / or body detection on the image information to determine the occupants in the cabin;

[0052] The first bleeding condition determination subunit is used to perform a blood test on the face and / or body surface of the occupant to determine the bleeding condition of the occupant in the cabin.

[0053] In a possible implementation, the bleeding detection unit is used to detect whether the occupant is bleeding based on the image information based on blood color information and blood flow shape information.

[0054] In a possible implementation, the bleeding detection unit includes:

[0055] a body surface area detection subunit, configured to detect a body surface area of ​​an occupant in the cabin based on the image information;

[0056] A detection area division subunit, used for dividing the body surface area of ​​the occupant into a plurality of detection areas;

[0057] A regional detection result determination subunit, used for detecting blood information in each detection area to obtain a regional detection result of each detection area;

[0058] The second bleeding condition determination subunit is used to determine the bleeding condition of the occupant based on the regional detection results of each of the detection areas.

[0059] In a possible implementation, the body surface area detection subunit is used to detect the face surface area of ​​the occupant in the cabin based on the image information;

[0060] The detection area division subunit is used to divide the facial surface area of ​​the occupant into multiple detection areas.

[0061] In a possible implementation, the area detection result determination subunit is used to determine a first confidence level of bleeding in each detection area based on the shape and area of ​​the blood flow in each detection area; determine whether there is a connected blood flow between adjacent detection areas; in response to determining that a first detection area in the detection area has a connected blood flow with an adjacent second detection area, increase the confidence levels of the multiple first detection areas and the second detection area to a second confidence level;

[0062] The second bleeding situation determination subunit is used to determine that the occupant is bleeding when the first confidence level or the second confidence level exceeds a confidence level threshold; and to determine the severity of the bleeding based on the area of ​​blood flow in each detection area, wherein the severity of the bleeding is positively correlated with the sum of the areas of blood flow in each of the detection areas.

[0063] In a possible implementation, the bleeding detection unit includes:

[0064] a bleeding part detection subunit, for determining a bleeding body part and a direction of blood flow in response to detecting bleeding of an occupant in the cabin based on the image information;

[0065] The bleeding site detection subunit is used to take the body site where the starting end of the blood flow is located as the bleeding site based on the bleeding body site and the direction of the blood flow.

[0066] In a possible implementation manner, the device further includes:

[0067] a body posture determination unit, configured to determine the body posture of the cabin occupant based on the image information;

[0068] The abnormal body posture determining unit is used to determine that the body posture of the cabin occupant is an abnormal body posture when the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds a set duration.

[0069] In a possible implementation manner, the device further includes:

[0070] The fracture condition detection unit is used to determine whether the cabin occupant has a fracture condition when it is determined that the body posture of the cabin occupant is a preset fracture posture.

[0071] In a possible implementation manner, the device further includes:

[0072] A vital sign index determining unit is used to determine the vital sign index of the occupant based on the image information, wherein the vital sign index includes at least one of the following:

[0073] Respiratory rate, blood pressure, heart rate;

[0074] The vital sign indicator sending unit is used to send the vital sign indicator to the emergency call center.

[0075] In a possible implementation manner, the device further includes:

[0076] an injury severity level determination unit, configured to determine the injury severity level of the cabin occupant based on at least one of the determined bleeding condition, abnormal body posture, and vital sign index of the occupant;

[0077] The injury severity level sending unit is used to send the injury severity level to an emergency call center.

[0078] According to one aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to call the instructions stored in the memory to execute the above method.

[0079] According to one aspect of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor.

[0080] In the disclosed embodiment, in response to the emergency call being triggered, the image information of the occupants in the cabin is obtained, and based on the image information, the bleeding of the occupants in the cabin is detected, and then in response to the bleeding, the bleeding is sent to the emergency call center. In this way, the injuries of the occupants in the accident can be determined, so that the emergency call center can reasonably dispatch rescue forces according to the injuries of the occupants in the accident, and shorten or omit the inquiry process of the call center personnel in the scene of serious bleeding, and rescue is carried out every minute.

[0081] It should be understood that the above general description and the following detailed description are exemplary and explanatory only and do not limit the present disclosure. Other features and aspects of the present disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0083] Figure 1 A flowchart showing a method for sending information according to an embodiment of the present disclosure is shown;

[0084] Figure 2 A block diagram showing an information sending device according to an embodiment of the present disclosure;

[0085] Figure 3 A block diagram of an electronic device according to an embodiment of the present disclosure is shown;

[0086] Figure 4 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0087] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0088] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0089] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0090] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0091] As described in the background technology, emergency call services can shorten rescue time and reduce the mortality rate of rescued people in vehicle accidents. However, in related technologies, it is difficult to determine the extent of the accident damage after the accident occurs, and it is even more difficult to confirm the casualties of the people in the car. When there are many emergency calls to the rescue center, the rescue center cannot reasonably dispatch rescue forces.

[0092] In the disclosed embodiment, in response to the emergency call being triggered, the image information of the occupants in the cabin is obtained, and based on the image information, the bleeding of the occupants in the cabin is detected, and then in response to the bleeding, the bleeding is sent to the emergency call center. In this way, the injuries of the occupants in the accident can be determined, so that the emergency call center can reasonably dispatch rescue forces according to the injuries of the occupants in the accident, and shorten or omit the inquiry process of the call center personnel in the scene of serious bleeding, and rescue is carried out every minute.

[0093] In one possible implementation, the execution subject of the method may be an intelligent driving control device installed on a vehicle. In one possible implementation, the method may be executed by a terminal device or a server or other processing device. Among them, the terminal device may be a vehicle-mounted device, a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device or a wearable device, etc. Among them, the vehicle-mounted device may be a vehicle machine or a domain controller in a cabin, or may be a device host for executing an information sending method in an ADAS (Advanced Driving Assistance System), an OMS (Occupant Monitoring System) or a DMS (Driver Monitoring System). In some possible implementations, the information sending method may be implemented by a processor calling a computer-readable instruction stored in a memory.

[0094] For ease of description, in one or more embodiments of this specification, the execution subject of the method for a vehicle to send information to an emergency call center may be an on-board device in the vehicle. The following text takes the execution subject as an on-board device as an example to introduce the implementation of the method. It can be understood that the execution subject of the method as an on-board device is only an exemplary description and should not be understood as a limitation on the method. Figure 1 A flow chart showing a method for a vehicle to send information to an emergency call center according to an embodiment of the present disclosure is shown. Figure 1 As shown, the method for a vehicle to send information to an emergency call center includes:

[0095] In step S11, in response to the emergency call being triggered, image information of the occupants in the cabin is acquired;

[0096] The image information here is the image information of the occupants in the vehicle cabin. The vehicle here can be at least one of the types of vehicles such as private cars, shared cars, online-hailing cars, taxis, trucks, etc. The present disclosure does not limit the specific type of the vehicle.

[0097] The image information here may be image information of the area where the passengers are located in the cabin, and the image information may be collected by an on-board image acquisition device installed inside or outside the cabin of the vehicle, and the on-board image acquisition device may be a vehicle-mounted camera or an image acquisition device equipped with a camera. The camera may be a camera for collecting image information inside the vehicle or a camera for collecting image information outside the vehicle.

[0098] For example, the camera may include a camera in the DMS and / or a camera in the OMS, etc., which can be used to collect image information inside the vehicle; the camera may also include a camera in the ADAS, which can be used to collect image information outside the vehicle. Of course, the vehicle-mounted image acquisition device may also be a camera in other systems, or may also be a separately configured camera, and the embodiments of the present disclosure do not limit the specific vehicle-mounted image acquisition device.

[0099] The carrier of the image information here can be a two-dimensional image or video. For example, the image information can specifically be a visible light image / video, or an infrared light image / video; it can also be a three-dimensional image composed of a point cloud scanned by a radar, etc. It can be determined according to the actual application scenario, and the present disclosure does not limit this.

[0100] The image information collected by the vehicle-mounted image acquisition device can be obtained through the communication connection established with the vehicle-mounted image acquisition device. In one example, the vehicle-mounted image acquisition device can transmit the collected image information to the vehicle-mounted controller or remote server through a bus or a wireless communication channel in real time, and the vehicle-mounted controller or remote server can receive the real-time image information through the bus or the wireless communication channel.

[0101] In step S12, based on the image information, the bleeding condition of the occupant in the cabin is detected;

[0102] Whether there is blood on the occupant can be detected based on image processing technology to determine whether the occupant is bleeding. In one example, the bleeding of the occupant can be detected by a neural network, or the blood in the image can be detected by target detection technology such as threshold segmentation to detect the bleeding of the occupant in the cabin. For the specific implementation of detecting the bleeding of the occupant, please refer to the possible implementation provided by the present disclosure, which will not be described in detail here.

[0103] In step S13, in response to detecting the bleeding situation, the bleeding situation is sent to an emergency call center.

[0104] There can be many specific ways to implement the bleeding situation sent to the emergency call center, for example, whether there is bleeding situation among the passengers in the cabin or not; or, when there is bleeding situation, more specific bleeding situation can also be sent, for example, the specific location of bleeding, the severity of bleeding, etc.

[0105] Therefore, by sending the bleeding situation to the emergency call center, the emergency call center can determine whether the initiator of the emergency call is bleeding, and when it is determined that there is bleeding, provide targeted rescue measures, such as carrying corresponding hemostatic supplies, blood transfusion supplies, and dispatching additional doctors to deal with bleeding situations, etc.

[0106] In the disclosed embodiment, in response to the emergency call being triggered, the image information of the occupants in the cabin is obtained, and based on the image information, the bleeding of the occupants in the cabin is detected, and then in response to the bleeding, the bleeding is sent to the emergency call center. In this way, the injuries of the occupants in the accident can be determined, so that the emergency call center can reasonably dispatch rescue forces according to the injuries of the occupants in the accident, and shorten or omit the inquiry process of the call center personnel in the scene of serious bleeding, and rescue is carried out every minute.

[0107] In a possible implementation, detecting the bleeding condition of the occupant in the cabin based on the image information includes: performing face detection and / or body detection on the image information to determine the occupant in the cabin; performing blood detection on the face and / or body surface of the occupant to determine the bleeding condition of the occupant in the cabin.

[0108] After obtaining the image information in the cabin, human body detection and / or face detection can be performed in the cabin based on the image information to obtain the human body detection result and / or face detection result in the cabin, and the occupant detection result in the cabin can be obtained based on the human body detection result and / or face detection result in the cabin. For example, the human body detection result and / or face detection result in the cabin can be used as the occupant detection result in the cabin. For another example, the occupant detection result in the cabin can be obtained after processing the human body detection result and / or face detection result in the cabin.

[0109] In the disclosed embodiment, human body detection and / or face detection are performed in the cabin to obtain human body detection results and / or face detection results in the cabin, and the detection results include position information of the human body and / or face. For example, when one occupant is detected, the occupant detection result includes the position information of the occupant; when multiple occupants are detected, the occupant detection result may include the position information of each detected occupant.

[0110] The position information of the occupant may be represented by the position information of the occupant's boundary box. Then, in the image selected by the boundary box, a blood test is performed on the occupant. Alternatively, the position information of the occupant may be represented by the position information of the occupant's boundary outline. Then, in the image surrounded by the boundary outline, a blood test is performed on the occupant.

[0111] Based on face detection, the position of the occupant's face can be obtained. When the face is detected, a blood test can be performed on the occupant's face to determine the bleeding condition of the occupant in the cabin; based on body detection, the position of the occupant's body can be obtained. When the body is detected, a blood test can be performed on the occupant's body surface to determine the bleeding condition of the occupant in the cabin.

[0112] In the disclosed embodiment, the occupants in the cabin are determined by performing face detection and / or body detection on the image information, and then blood tests are performed on the faces and / or body surfaces of the occupants to determine the bleeding conditions of the occupants in the cabin. Thus, first performing face detection and / or body detection on the image information and then performing blood tests on the faces and / or body surfaces of the occupants can not only narrow the image range for subsequent blood tests and improve the detection efficiency, but also reduce the interference of other areas of the occupants' bodies on the blood tests and improve the accuracy of the bleeding condition detection.

[0113] A specific implementation method of blood detection may be to detect based on blood color information and blood flow shape information. Then, in a possible implementation method, detecting the bleeding of the occupant in the cabin based on the image information includes: based on the blood color information and blood flow shape information, detecting whether the occupant is bleeding based on the image information.

[0114] When a passenger bleeds, the color of the blood is often bright red. In computers, the representation of color is achieved by defining color parameters in a color space. The commonly used color space is the red, green, and blue (RGB) color space. In addition, based on the standards established by the International Commission on Illumination (Commission Internationale de L'Eclairage, CIE) standard colorimetry system, there are also color spaces such as HSL, LMS, CMYK, CIE YUV, HSB (HSV), and YCbCr in related technologies. The expression of color space is diverse, different color spaces may have different characteristics, and color parameters of different color spaces can be converted to each other.

[0115] According to the definition of color parameters in different color spaces, the corresponding color parameters can be parsed from the image information. When an image is stored in a computer, it will be stored in a default color space. The default color space of most images in the computer is the RGB color space, which is divided into three color components: red (R), green (G), and blue (B). The value range of each color component is 0 to 255. When the computer reads the image information from the storage medium, it reads the image information through digital image processing technology, that is, it can obtain the three-dimensional components of each pixel in the image information in the default color space, that is, the color parameters of the image information in the default color space are obtained.

[0116] Each pixel has a color parameter. Different color parameters represent different colors. Therefore, the color of the pixel can be determined based on the color parameter. For the color of blood, its color parameter can be a range. In one example, taking the RGB color space as an example, the range of the blood color parameter can be expressed as (150,0,0)-(250,50,50). When the color range of the pixel is within this range, it can be considered to be the color of blood. Further, it can be verified based on the shape of the blood.

[0117] In addition, the detection of bleeding can also be achieved based on neural network technology. In the process of image processing using neural network technology, image features are often extracted through image convolution operations. In this operation, the pixel values ​​of the image are extracted. Then, the color information of the blood will be extracted as a high-dimensional feature representation. The neural network can determine the high-dimensional features belonging to the blood color based on the high-dimensional features, and then detect bleeding.

[0118] Since the color of the occupant's clothing, accessories and other attachments may be similar to the color of blood, it is possible to further determine whether the occupant is bleeding based on the shape of the blood flow. The shape of the blood flow can be obtained based on the real shape of the blood flow in the image.

[0119] Blood detection can be implemented based on a deep neural network. The neural network used for blood detection can be, for example, a Seq2Seq model based on an attention mechanism, a Tensorflow model, etc. The neural network can be a trained network, or it can be trained based on the characteristics of the image information of the occupant bleeding using an image dataset containing the occupant bleeding in the image content. The neural network is trained by marking the bleeding area in the image dataset, so that the neural network has a high accuracy rate when detecting blood and can accurately detect blood on the face and / or body surface of the occupant.

[0120] In the embodiment of the present disclosure, by detecting whether the occupant is bleeding based on the image information based on the blood color information and the blood flow shape information, the bleeding condition of the occupant in the cabin can be accurately detected.

[0121] In one possible implementation, detecting the bleeding condition of the occupant in the cabin based on the image information includes: detecting the body surface area of ​​the occupant in the cabin based on the image information; dividing the body surface area of ​​the occupant into a plurality of detection areas; detecting blood information in each of the detection areas to obtain a regional detection result of each of the detection areas; and determining the bleeding condition of the occupant based on the regional detection result of each of the detection areas.

[0122] Based on the image information, the body surface area of ​​the cabin occupants can be detected. The body surface area can be represented based on the coordinates in the image. The body surface area can be divided into multiple detection areas. There are many ways to divide the detection area. For example, the body surface area can be divided by grids. This division method can divide the exposed part of the body surface (such as the face, neck, etc.) into grids of the same area. For example, the body surface area can also be divided according to the human body parts in the body surface. The arms on the body surface can be divided into a detection area, the chest can be divided into a detection area, and the abdomen can be divided into a detection area, and so on. When dividing the body surface area according to the human body parts, the human body key point detection can be performed on the human body to obtain the key points used to identify the human body parts, and then the body surface area can be divided according to the key points to obtain multiple detection areas. In addition, there can be many ways to divide the human body surface area, and the present disclosure does not limit this.

[0123] After obtaining multiple detection areas, blood information can be detected in each detection area. The specific method of detecting blood information can refer to the possible implementation methods provided in the present disclosure. For example, blood can be detected based on blood color and blood flow shape, or blood can be detected through a trained neural network, which will not be elaborated here.

[0124] After detecting blood information in each detection area, the regional detection result of each detection area can be obtained. The regional detection result can be the presence or absence of bleeding. When bleeding exists, it can also be specific to the area where bleeding exists and the specific position information of the blood flow in the detection area can be detected.

[0125] Then, based on the regional detection results of each detection area, the regional detection results of each detection area can be weighted and fused to determine the bleeding condition of the occupant; or, the detection results of each area can be combined to determine the confidence level and bleeding severity of the occupant. For details, please refer to the possible implementation methods provided in the present disclosure, which will not be elaborated here.

[0126] In the embodiment of the present disclosure, the body surface area of ​​the occupant in the cabin is detected based on the image information; the body surface area of ​​the occupant is divided into a plurality of detection areas; blood information is detected in each detection area to obtain a regional detection result of each detection area, thereby determining the bleeding condition of the occupant based on the regional detection result of each detection area, thereby improving the accuracy of the determined bleeding condition.

[0127] In one possible implementation, detecting the body surface area of ​​the occupant in the cabin based on the image information includes: detecting the facial surface area of ​​the occupant in the cabin based on the image information; dividing the body surface area of ​​the occupant into a plurality of detection areas includes: dividing the facial surface area of ​​the occupant into a plurality of detection areas.

[0128] Based on the image information, the facial surface area of ​​the occupants in the cabin can be detected. The facial surface area can be represented based on the coordinates in the image. The facial surface area can be divided into multiple detection areas. There are many ways to divide the facial surface area. For example, the facial surface area can be divided by grids. The grids can be grids with the same area. In this way, the facial surface area can be divided by grids with the same area. For example, the facial surface area can also be divided according to the parts of the facial surface. The forehead can be divided into a detection area, the two sides of the nose can be divided into a detection area, the mouth and the following parts can be divided into a detection area, and so on. When the facial surface area is divided according to the facial parts, the facial key points can be detected on the facial surface to obtain the key points used to identify the facial parts, and then the facial surface area can be divided according to the key points to obtain multiple detection areas. In addition, there can be many ways to divide the facial surface area, and the present disclosure does not limit this.

[0129] In the embodiment of the present disclosure, the facial surface area of ​​the occupant in the cabin is detected based on the image information, and then the facial surface area of ​​the occupant is divided into multiple detection areas. Thus, the bleeding situation of the occupant's face is determined based on the area detection results of each detection area, thereby improving the accuracy of the determined bleeding situation.

[0130] In a possible implementation, the detecting of blood information in each of the detection areas to obtain regional detection results of each of the detection areas includes: determining a first confidence level that bleeding exists in each of the detection areas based on the shape and area of ​​the blood flow in each detection area; determining whether there is a connected blood flow between adjacent detection areas; in response to determining that a first detection area in the detection areas has a connected blood flow with an adjacent second detection area, raising the confidence levels of the multiple first detection areas and the second detection areas to a second confidence level; determining the bleeding situation of the occupant based on the regional detection results of each of the detection areas, includes: determining that the occupant is bleeding when the first confidence level or the second confidence level exceeds a confidence threshold; determining the severity of bleeding based on the area of ​​blood flow in each of the detection areas, the severity of bleeding being positively correlated with the area and the blood flow of each of the detection areas.

[0131] When detecting blood flow in image information based on image processing technology, it can be regarded as a binary classification problem of determining whether a pixel in the image belongs to blood flow. This can be achieved based on image segmentation technology in deep learning, so that the location of the pixel belonging to blood flow in the detection area can be obtained. Multiple pixels classified as blood flow are connected to form a blood flow area, that is, a blood flow shape. The area of ​​blood flow can be the area of ​​multiple pixels classified as blood flow in the image, or it can be converted into the actual area on the occupant's body surface.

[0132] Based on the shape and area of ​​the blood flow in each detection area, the first confidence level of the presence of bleeding in each detection area can be determined, which can be specifically determined based on a neural network, and the first confidence level represents the credibility of the presence of blood flow in a single detection area. The first confidence level can be positively correlated with the area of ​​the blood flow in the area, that is, the larger the area, the higher the first confidence level; the closer the shape of the blood flow in the detection area is to the shape of the real blood flow, the higher the first confidence level.

[0133] After obtaining the first confidence level of each detection area, it is possible to further determine whether there is connected blood flow between the detection areas. Specifically, it can be determined based on the position of the blood determined in each detection area. The position of the blood in each detection area may be the position in the image information. If the positions of the blood are adjacent in the image information, it can be determined that there is connected blood flow between the detection areas.

[0134] Since there is connected blood flow between the detection areas, it indicates that the bleeding area of ​​the occupant is larger than the blood flow area in a single detection area, so the credibility of the occupant's bleeding should be further improved. Therefore, in response to determining that there is connected blood flow between the first detection area and the adjacent second detection area in the detection area, the confidence of multiple first detection areas and the second detection area is increased to a second confidence level to improve the credibility of the bleeding in the first detection area and the second detection area.

[0135] For example, the first confidence levels of the first detection area and the second detection area are 0.6 and 0.7 respectively. When it is determined that there is a connected blood flow in the first detection area and the second detection area, the confidence levels of the first detection area and the second detection area can be increased to 0.7 and 0.8 respectively to obtain a second confidence level. It should be noted that the specific increase in the first confidence level can be determined based on actual needs, and this disclosure does not specifically limit this.

[0136] Since the confidence level can represent the credibility of the occupant's bleeding, a confidence threshold can be pre-set, and when the first confidence level or the second confidence level exceeds the confidence threshold, it is determined that the occupant is bleeding. The specific setting of the confidence threshold can be determined according to actual needs, and the present disclosure does not make specific limitations on this.

[0137] In addition, since the larger the blood flow area, the more severe the bleeding is, in one possible implementation, the severity of bleeding can be determined based on the blood flow area in each detection area, and the severity of bleeding is positively correlated with the sum of the blood flow areas of each of the detection areas.

[0138] In the disclosed embodiment, based on the shape and area of ​​the blood flow in each detection area, a first confidence level of the presence of bleeding in each detection area is determined; whether there is a connected blood flow between adjacent detection areas is determined; in response to determining that a first detection area in the detection area has a connected blood flow with an adjacent second detection area, the confidence levels of the multiple first detection areas and the second detection areas are increased to a second confidence level; and when the first confidence level or the second confidence level exceeds a confidence level threshold, it is determined that the occupant is bleeding. Thus, the accuracy of the determined bleeding situation can be improved. In addition, based on the area of ​​the blood flow in each detection area, the severity of the bleeding is determined, and the severity of the bleeding is sent to the emergency call center so that the emergency call center can promptly learn of the severity of the bleeding of the caller, reasonably dispatch rescue forces, and provide targeted rescue.

[0139] In one possible implementation, detecting bleeding of an occupant in the cabin based on the image information includes: in response to detecting bleeding of the occupant in the cabin based on the image information, determining the bleeding part of the body and the direction of blood flow; based on the bleeding part of the body and the direction of blood flow, taking the part of the body where the starting end of the blood flow is located as the bleeding part.

[0140] Based on the detection of key points of the human body, the body parts of the occupant's body surface can be determined, thereby, the body part where the blood is located can be determined. Since blood is fluid, the blood may cross multiple body parts after bleeding from a certain part. Therefore, the direction of blood flow can be further determined. Based on the direction of blood flow, the body part where the starting end of the blood flow is located is regarded as the bleeding part.

[0141] In the process of determining the direction of blood flow, it can be determined based on multiple video frames in the image information. Blood detection is performed in multiple video frames. The direction of gradually increasing blood flow can be determined based on the blood flow in multiple video frames, and this direction can be used as the direction of blood flow.

[0142] In the disclosed embodiment, in response to detecting bleeding of the occupant in the cabin based on the image information, the bleeding body part and the direction of the blood flow are determined; based on the bleeding body part and the direction of the blood flow, the body part where the starting end of the blood flow is located is used as the bleeding part. Thus, the bleeding part can be accurately determined, and the bleeding part can be sent to the emergency call center as the bleeding situation, so that the emergency call center can identify the bleeding part of the caller, and the severity of the bleeding can be determined based on the bleeding part, and the rescue force can be reasonably dispatched to provide targeted rescue.

[0143] In a possible implementation, the method further includes: determining the body posture of the occupant in the cabin based on the image information; and determining that the body posture of the occupant in the cabin is an abnormal body posture when the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds a set duration.

[0144] In the disclosed embodiment, the body posture of the cabin occupant can be determined based on the image information. For example, the body posture of the occupant can be determined by image recognition technology. Body posture detection can be determined based on human key detection. As an example of this implementation, multiple human key points to be detected can be pre-set. For example, 17 key points can be set in the human skeleton to indicate various parts of the human body. By detecting these 17 key points, the positional relationship between the various parts of the human body can be obtained according to the positional relationship between the 17 key points. The positional relationship between the various parts of the human body is the specific manifestation of body posture.

[0145] As an example of this implementation, the image information can be input into the backbone network, and the image information is extracted through the backbone network to obtain a feature map, and then the position of the key points of the human body is detected based on the feature map to obtain the human body posture. The backbone network can adopt a network structure such as ResNet, MobileNet, etc., which is not limited here.

[0146] After determining the body posture of the cabin occupant, it can be determined whether the body posture is a preset abnormal body posture. When it is determined that the body posture is a preset abnormal body posture, the health status of the cabin occupant is determined to be abnormal. The preset abnormal body posture includes at least one of the following: the body is tilted to one side, the head is tilted downward, and the face is facing up. Since the body posture of the occupant can reflect the user's physical health status to a certain extent, when an accident occurs, the occupant is often unable to maintain a straight posture when injured, and will present abnormal postures such as the body tilted to one side, the head tilted downward, or the face facing up. These body postures can accurately indicate that the user's current health status is abnormal.

[0147] Therefore, these abnormal body postures can be set in advance. After the body posture of the occupants in the cabin is determined, it can be judged whether the physical condition of the occupants in the cabin is the preset abnormal body posture. When it is determined that the body posture is the preset abnormal body posture, it is determined that the health condition of the occupants in the cabin is abnormal.

[0148] In addition, in order to improve the accuracy of abnormal condition detection, the body posture of the occupant in the cabin can be determined to be an abnormal body posture when the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds the set duration.

[0149] In the disclosed embodiment, the body posture of the cabin occupant is determined based on the image information; when the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds the set duration, the body posture of the cabin occupant is determined to be an abnormal body posture. In this way, the abnormal situation of the occupant can be accurately determined, so as to accurately determine the severity level of the occupant's injury later, and send the severity level of the occupant's injury to the emergency call center so that the emergency call center can give priority to rescuing seriously injured passengers.

[0150] In a possible implementation, the method further includes: determining that the occupant in the cabin has a fracture when it is determined that the body posture of the occupant in the cabin is a preset fracture posture.

[0151] When a occupant has a fracture, his / her body posture is obviously different from a normal body posture. For example, if a non-joint part of the occupant is bent, it can be confirmed that the occupant has a fracture. For example, if a non-joint part of the arm is bent, it can be determined that the occupant has a fracture in the arm. For another example, if a non-joint part of the leg is bent, it can also be determined that the occupant has a fracture in the leg.

[0152] In a possible implementation, the method further includes: determining the vital sign indicators of the occupant based on the image information, the vital sign indicators including at least one of the following: respiratory rate, blood pressure, heart rate; and sending the vital sign indicators to an emergency call center.

[0153] Vital sign indicators can be determined based on physiological characteristic sensing information collected by physiological characteristic sensors. For example, taking the life characteristic sensor as a millimeter wave radar, the principle of millimeter wave radar for monitoring respiration and heart rate is to use the radar to emit electromagnetic waves and then detect the frequency of the echo signal to detect the respiration and heart rate of the occupant. In this example, the life characteristic sensing information is the echo signal of the millimeter wave radar. Millimeter wave radar can detect tiny vibrations and displacements of the human body by measuring the change in the phase of the echo signal. In one example, the heartbeat and breathing frequency can be determined based on the detection of the chest vibration amplitude.

[0154] After the vital sign indicators are determined, the vital sign indicators may be sent to an emergency call center so that the emergency call center can reasonably dispatch rescue forces and perform targeted rescue on the passengers.

[0155] In a possible implementation, the method further includes: determining the severity level of the injury of the occupant in the cabin based on at least one of the determined bleeding condition, abnormal body posture, and vital sign indicators of the occupant; and sending the severity level of the injury to an emergency call center.

[0156] The injury severity level is used to characterize the severity of the occupant's injury. The level may be divided into, for example, 0-10 levels, where the higher the level, the more severe the injury. Level 0 indicates that the occupant is not injured.

[0157] There can be one or more injury severity levels. For example, one injury level can be used to comprehensively represent the severity of the occupant's bleeding, abnormal body posture, vital signs, etc. Alternatively, multiple severity levels can be used to separately represent the severity of the occupant's injury. For example, the bleeding severity level, fracture severity level, vital signs weakness level, etc. can be preset.

[0158] The severity of bleeding can be determined based on the area and location of bleeding. The area of ​​bleeding is positively correlated with the severity of bleeding. The more severe the bleeding is, the more severe it is. The severity of fractures is positively correlated with the degree of bending of the human skeleton and the number of fractured bones. The more severe the bleeding is, the more severe it is, if the fracture is located in a vital area such as the head. The level of vital sign weakness is negatively correlated with the vital sign indicators. The lower the respiratory rate, blood pressure, and heart rate, the higher the level of vital sign weakness.

[0159] When an injury severity level is used to comprehensively represent the severity of the occupant's bleeding condition, abnormal body posture, vital signs indicators, etc., the severity levels of the occupant's bleeding condition, abnormal body posture, and vital signs indicators can be weighted averaged to obtain a comprehensive injury severity level; or, the injury severity level can be determined based on the most serious of the occupant's bleeding condition, abnormal body posture, and vital signs indicators.

[0160] In the disclosed embodiment, the severity level of the injury of the cabin occupant is determined based on at least one of the determined bleeding condition, abnormal body posture, and vital sign indicators of the occupant, and the severity level of the injury is sent to the emergency call center. As a result, the emergency call center can give priority to rescuing the occupant of the caller with a high severity level of injury according to the severity level of the injury, reduce or omit the inquiry process, provide faster rescue, and reduce personal and property losses.

[0161] An application scenario of an embodiment of the present disclosure is described below. In this application scenario, after an accident occurs, an emergency call is triggered, and then image information of the occupants in the cabin is obtained. If it is detected that the occupants in the cabin have no obvious bleeding and their body posture is normal, the casualties are judged to be minor. After the emergency call is connected, the call center briefly confirms with the occupants in the car and confirms that no additional assistance is needed.

[0162] Another application scenario of the embodiment of the present disclosure is described below. In this application scenario, after an accident occurs, an emergency call is triggered, and then the image information of the occupants in the cabin is obtained. It is detected that the occupants in the cabin are bleeding heavily on the body surface, their limbs are still, and their breathing is weak. The severity level of the injury is determined to be high, and the severity level of the injury is sent to the emergency call center. The emergency call directly dispatches an ambulance to the location of the accident, and the call center personnel communicate with the car to further understand the situation.

[0163] It can be understood that the above-mentioned various method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle logic. Due to space limitations, the present disclosure will not repeat them. It can be understood by those skilled in the art that in the above-mentioned method of the specific implementation method, the specific execution order of each step should be determined according to its function and possible internal logic.

[0164] In addition, the present disclosure also provides a device, an electronic device, a computer-readable storage medium, and a program for a vehicle to send information to an emergency call center. The above can be used to implement any information sending method provided by the present disclosure. The corresponding technical solutions and descriptions are referred to the corresponding records in the method part and will not be repeated here.

[0165] Figure 2 A block diagram of an information sending device according to an embodiment of the present disclosure is shown as follows: Figure 2 As shown, the device 20 comprises:

[0166] An image information acquisition unit 21 is used to acquire image information of passengers in the cabin in response to an emergency call being triggered;

[0167] a bleeding condition detection unit 22, configured to detect the bleeding condition of the occupant in the cabin based on the image information;

[0168] The bleeding situation sending unit 23 is used for sending the bleeding situation to an emergency call center in response to detecting the bleeding situation.

[0169] In a possible implementation, the bleeding detection unit includes:

[0170] An occupant detection subunit, configured to perform face detection and / or body detection on the image information to determine the occupants in the cabin;

[0171] The first bleeding condition determination subunit is used to perform a blood test on the face and / or body surface of the occupant to determine the bleeding condition of the occupant in the cabin.

[0172] In a possible implementation, the bleeding detection unit is used to detect whether the occupant is bleeding based on the image information based on blood color information and blood flow shape information.

[0173] In a possible implementation, the bleeding detection unit includes:

[0174] a body surface area detection subunit, configured to detect a body surface area of ​​an occupant in the cabin based on the image information;

[0175] A detection area division subunit, used for dividing the body surface area of ​​the occupant into a plurality of detection areas;

[0176] A regional detection result determination subunit, used for detecting blood information in each detection area to obtain a regional detection result of each detection area;

[0177] The second bleeding condition determination subunit is used to determine the bleeding condition of the occupant based on the regional detection results of each of the detection areas.

[0178] In a possible implementation, the body surface area detection subunit is used to detect the face surface area of ​​the occupant in the cabin based on the image information;

[0179] The detection area division subunit is used to divide the facial surface area of ​​the occupant into multiple detection areas.

[0180] In a possible implementation, the area detection result determination subunit is used to determine a first confidence level of bleeding in each detection area based on the shape and area of ​​the blood flow in each detection area; determine whether there is a connected blood flow between adjacent detection areas; in response to determining that a first detection area in the detection area has a connected blood flow with an adjacent second detection area, increase the confidence levels of the multiple first detection areas and the second detection area to a second confidence level;

[0181] The second bleeding situation determination subunit is used to determine that the occupant is bleeding when the first confidence level or the second confidence level exceeds a confidence level threshold; and to determine the severity of the bleeding based on the area of ​​blood flow in each detection area, wherein the severity of the bleeding is positively correlated with the sum of the areas of blood flow in each of the detection areas.

[0182] In a possible implementation, the bleeding detection unit includes:

[0183] a bleeding part detection subunit, for determining a bleeding body part and a direction of blood flow in response to detecting bleeding of an occupant in the cabin based on the image information;

[0184] The bleeding site detection subunit is used to take the body site where the starting end of the blood flow is located as the bleeding site based on the bleeding body site and the direction of the blood flow.

[0185] In a possible implementation manner, the device further includes:

[0186] a body posture determination unit, configured to determine the body posture of the cabin occupant based on the image information;

[0187] The abnormal body posture determining unit is used to determine that the body posture of the cabin occupant is an abnormal body posture when the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds a set duration.

[0188] In a possible implementation manner, the device further includes:

[0189] The fracture condition detection unit is used to determine whether the cabin occupant has a fracture condition when it is determined that the body posture of the cabin occupant is a preset fracture posture.

[0190] In a possible implementation manner, the device further includes:

[0191] A vital sign index determining unit is used to determine the vital sign index of the occupant based on the image information, wherein the vital sign index includes at least one of the following:

[0192] Respiratory rate, blood pressure, heart rate;

[0193] The vital sign indicator sending unit is used to send the vital sign indicator to the emergency call center.

[0194] In a possible implementation manner, the device further includes:

[0195] an injury severity level determination unit, configured to determine the injury severity level of the cabin occupant based on at least one of the determined bleeding condition, abnormal body posture, and vital sign index of the occupant;

[0196] The injury severity level sending unit is used to send the injury severity level to an emergency call center.

[0197] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. Its specific implementation and technical effects can refer to the description of the above method embodiments. For the sake of brevity, they will not be repeated here.

[0198] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0199] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to call the instructions stored in the memory to execute the above method.

[0200] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0201] The electronic device may be provided as a terminal, a server, or a device in other forms.

[0202] Figure 3A block diagram of an electronic device 800 according to an embodiment of the present disclosure is shown. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like.

[0203] Reference Figure 3 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0204] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0205] The memory 804 is configured to store various types of data to support operations on the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0206] The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 800.

[0207] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0208] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0209] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0210] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open / closed state of the electronic device 800, the relative positioning of the components, such as the display and keypad of the electronic device 800, and the sensor assembly 814 can also detect the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a complementary metal oxide semiconductor (CMOS) or a charge coupled device (CCD) image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0211] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as a wireless network (WiFi), a second generation mobile communication technology (2G) or a third generation mobile communication technology (3G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0212] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0213] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 804 including computer program instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above method.

[0214] Figure 4 1 is a block diagram of an electronic device 1900 according to an embodiment of the present disclosure. For example, the electronic device 1900 may be provided as a server. Figure 4 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0215] The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output (I / O) interface 1958. The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as a Microsoft Server operating system (Windows Server 2003). TM), a graphical user interface operating system launched by Apple (Mac OSX TM ), a multi-user, multi-process computer operating system (Unix TM ), a free and open source Unix-like operating system (Linux TM ), an open source Unix-like operating system (FreeBSD TM ) or similar.

[0216] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the electronic device 1900 to perform the above method.

[0217] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0218] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, (but not limited to) an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0219] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0220] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0221] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0222] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0223] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0224] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0225] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK) and the like.

[0226] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for a vehicle to send information to an emergency call center, characterized in that: include: In response to an emergency call being triggered, acquiring image information of the occupants in the cabin; Based on the image information, detecting bleeding of the occupants in the cabin; In response to detecting the bleeding condition, transmitting the bleeding condition to an emergency call center; The detecting the bleeding condition of the occupant in the cabin based on the image information includes: Based on the image information, detecting a body surface area of ​​an occupant in the cabin; Dividing the body surface area of ​​the occupant into a plurality of detection areas; Detecting blood information in each of the detection areas to obtain a regional detection result of each of the detection areas; determining the bleeding condition of the occupant based on the regional detection results of each of the detection areas; The detecting of blood information in each of the detection areas to obtain the area detection results of each of the detection areas includes: Determining a first confidence level of the presence of bleeding in each detection area based on the shape and area of ​​the blood flow in each detection area; Determine whether there is a connected blood flow between adjacent detection areas; In response to determining that a first detection area in the detection areas has a connected blood flow with an adjacent second detection area, raising the confidence levels of the plurality of first detection areas and the second detection area to a second confidence level; The determining the bleeding condition of the occupant based on the regional detection results of each of the detection areas includes: When the first confidence level or the second confidence level exceeds a confidence level threshold, determining that the occupant is bleeding; The severity of bleeding is determined based on the area of ​​blood flow in each detection region, and the severity of bleeding is positively correlated with the sum of the areas of blood flow in each detection region.

2. The method according to claim 1, characterized in that: The detecting the bleeding condition of the occupant in the cabin based on the image information includes: Performing face detection and / or body detection on the image information to determine the occupants in the cabin; A blood test is performed on the face and / or body of the occupant to determine the bleeding condition of the occupant in the cabin.

3. The method according to any one of claims 1 or 2, characterized in that: The detecting the bleeding condition of the occupant in the cabin based on the image information includes: Based on the blood color information and the blood flow shape information, it is detected based on the image information whether the occupant is bleeding.

4. The method according to claim 1, characterized in that The detecting, based on the image information, a body surface area of ​​the occupant in the cabin includes: Detecting a facial surface area of ​​an occupant in the cabin based on the image information; The dividing the body surface area of ​​the occupant into a plurality of detection areas comprises: The facial surface area of ​​the occupant is divided into a plurality of detection areas.

5. The method according to any one of claims 1-2, characterized in that: The detecting the bleeding condition of the occupant in the cabin based on the image information includes: In response to detecting bleeding of the occupant in the cabin based on the image information, determining a bleeding body part and a direction of blood flow; Based on the bleeding body part and the direction of blood flow, the body part where the starting end of the blood flow is located is used as the bleeding part.

6. The method according to any one of claims 1-2, characterized in that: The method further comprises: Determining the body posture of the occupant in the cabin according to the image information; When the body posture is a preset abnormal body posture and the duration of the abnormal body posture exceeds a set duration, it is determined that the body posture of the cabin occupant is an abnormal body posture.

7. The method according to claim 6, characterized in that: The method further comprises: When it is determined that the body posture of the cabin occupant is a preset fracture posture, it is determined that the cabin occupant has a fracture.

8. The method according to any one of claims 1-2, characterized in that: The method further comprises: Determine the vital sign index of the occupant based on the image information, where the vital sign index includes at least one of the following: Respiratory rate, blood pressure, heart rate; The vital sign indicator is sent to an emergency call center.

9. The method according to any one of claims 1-2, characterized in that: The method further comprises: Determining the severity level of the injury of the occupant in the cabin based on at least one of the determined bleeding condition, abnormal body posture, and vital sign indicators of the occupant; The injury severity level is transmitted to an emergency call center.

10. A device for a vehicle to send information to an emergency call center, characterized in that: include: An image information acquisition unit, configured to acquire image information of passengers in the cabin in response to an emergency call being triggered; a bleeding condition detection unit, used to detect the bleeding condition of the occupant in the cabin based on the image information; a bleeding situation sending unit, configured to send the bleeding situation to an emergency call center in response to detecting the bleeding situation; The bleeding situation detection unit comprises: a body surface area detection subunit, configured to detect a body surface area of ​​an occupant in the cabin based on the image information; A detection area division subunit, used for dividing the body surface area of ​​the occupant into a plurality of detection areas; A regional detection result determination subunit, used for detecting blood information in each detection area to obtain a regional detection result of each detection area; a second bleeding condition determination subunit, configured to determine the bleeding condition of the occupant based on the regional detection results of each of the detection areas; The area detection result determination subunit is used to determine a first confidence level of bleeding in each detection area based on the shape and area of ​​the blood flow in each detection area; determine whether there is a connected blood flow between adjacent detection areas; and in response to determining that a first detection area in the detection area has a connected blood flow with an adjacent second detection area, increase the confidence levels of the plurality of first detection areas and the second detection area to a second confidence level; The second bleeding situation determination subunit is used to determine that the occupant is bleeding when the first confidence level or the second confidence level exceeds a confidence level threshold; and to determine the severity of the bleeding based on the area of ​​blood flow in each detection area, wherein the severity of the bleeding is positively correlated with the sum of the areas of blood flow in each of the detection areas.

11. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the method described in any one of claims 1 to 9.

12. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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