CN112511746A - In-vehicle photographing processing method and device and computer readable storage medium - Google Patents
In-vehicle photographing processing method and device and computer readable storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/61—Control of cameras or camera modules based on recognised objects
- H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
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Abstract
The application discloses a method and a device for processing in-vehicle photographing and a computer readable storage medium, which are used for solving the problem of poor experience of the existing in-vehicle photographing user. The scheme provided by the application comprises the following steps: acquiring videos of relevant vehicle internal conditions shot by a first vehicle camera in real time; performing character action feature recognition on the video; and when the character action characteristics are recognized from the video, performing photographing operation to obtain a photo containing the character action characteristics. According to the scheme of the embodiment of the application, automatic photographing operation is executed after the character action characteristics of the video in the vehicle are identified, so that the user experience is improved.
Description
Technical Field
The application relates to the technical field of vehicle networking, in particular to a method and a device for processing in-vehicle photographing and a computer readable storage medium.
Background
With the rapid development of the internet of vehicles, the vehicle-mounted camera not only can realize real-time driving recording and guard for 24-hour sentries, but also can be used for identifying vehicles, pedestrians and roadblocks in the aspect of automatic driving. The camera is in the application of car networking, and the technical scene is more and more extensive, and the technique is more and more mature.
Present camera is shot mostly through vehicle event data recorder in the car, however, this kind generally need manual button or pronunciation to send the instruction of shooing, and the initiative starts the function of shooing and can influence driver's attention, causes certain danger to driving safety. And the expression actions of people participating in the shooting in the car cannot be well controlled, such as smiling mouth shape, limb actions and the like are too deliberate, and the shooting gesture is obvious. From this, the current mode of shooing in the car can bring not good user experience for the user.
Therefore, how to improve the safety of the vehicle when photographing in the vehicle and improve the user experience is a technical problem that needs to be solved urgently at present.
Disclosure of Invention
The embodiment of the application aims to provide an in-vehicle photographing processing method and device and a computer readable storage medium, which are used for solving the problem that the user experience is not good in the existing in-vehicle photographing mode.
In order to solve the above technical problem, the present specification is implemented as follows:
in a first aspect, a method for processing a photo in a vehicle is provided, which includes:
acquiring videos of relevant vehicle internal conditions shot by a first vehicle camera in real time;
performing character action feature recognition on the video;
and when the character action characteristics are recognized from the video, performing photographing operation to obtain a photo containing the character action characteristics.
The character motion features include character facial expression motions and/or character limb motions.
Optionally, performing character motion feature recognition on the video, including:
acquiring a current frame image of the video;
and inputting the current frame image into a preset first action recognition model to recognize whether the human action characteristics exist in the current frame image.
Optionally, performing character motion feature recognition on the video, including:
acquiring a current multi-frame image of the video;
and inputting the current multi-frame image into a predetermined second motion recognition model to recognize whether a specific human motion characteristic exists in the current multi-frame image.
Optionally, before performing character motion feature recognition on the video, the method further includes:
the method comprises the steps of obtaining a sensitivity level for triggering recognition of the character action features, wherein the sensitivity level corresponds to the action amplitude of the character action features, and the higher the sensitivity level is, the larger the action amplitude of the character action features required for triggering the recognition is.
Optionally, when the character motion feature is identified from the video, performing a photographing operation, including:
when the character action characteristics are identified from the video, starting a customized photographing function, and executing a photographing operation by a second in-vehicle camera according to the customized photographing function; or
When the character action characteristics are identified from the video, a photographing instruction is sent to the first in-vehicle camera or the second in-vehicle camera, so that the first in-vehicle camera or the second in-vehicle camera executes photographing operation according to the photographing instruction.
Optionally, the method further includes:
and saving or sharing the photo to a social platform.
In a second aspect, an in-vehicle photographing processing system is provided, which comprises an in-vehicle camera, an intelligent networking system and a customized photographing application, wherein the customized photographing application is installed in the intelligent networking system,
the camera in the vehicle is used for shooting videos related to the internal conditions of the vehicle in real time;
the intelligent network system is used for acquiring videos shot by the camera in the vehicle in real time, identifying character action characteristics of the videos and sending a shooting instruction to the customized shooting application when the character action characteristics are identified from the videos;
and the customized photographing application is used for executing the photographing operation of the customized function according to the photographing instruction and obtaining the photo containing the character action characteristics.
In a third aspect, an in-vehicle photographing processing apparatus is provided, which includes a processor and a processor electrically connected to the memory, wherein the memory stores a computer program executable by the processor, and the computer program implements the steps of the method according to the first aspect when executed by the processor.
In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method according to the first aspect.
In the embodiment of the application, videos of the internal conditions of the vehicle shot by the first in-vehicle camera are obtained in real time; performing character action feature recognition on the video; when the character action characteristics are identified from the video, the photographing operation is executed to obtain the photo containing the character action characteristics, so that the automatic photographing operation is executed after the character action characteristics of the in-vehicle video are identified, the driving safety of the vehicle is improved when the in-vehicle video is photographed, and the user experience is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart of a photographing processing method in a vehicle according to an embodiment of the present application.
Fig. 2 is a flowchart illustrating a human motion feature recognition step according to a first embodiment of the present application.
Fig. 3 is a flowchart illustrating a human motion feature recognition step according to a second embodiment of the present application.
Fig. 4 is a schematic flowchart of an example of an in-vehicle photographing processing method according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of the in-vehicle photographing processing system according to the embodiment of the application.
Fig. 6 is a schematic structural diagram of the in-vehicle photographing processing device according to the embodiment of the application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. The reference numbers in the present application are only used for distinguishing the steps in the scheme and are not used for limiting the execution sequence of the steps, and the specific execution sequence is described in the specification.
In order to solve the problems in the prior art, the embodiment of the application provides an in-vehicle photographing processing method which can be executed in a vehicle-mounted intelligent networking system. As shown in fig. 1, fig. 1 is a schematic flow chart of a photographing processing method in a vehicle according to an embodiment of the present application.
The method comprises the following steps:
and step 206, when the character action characteristics are recognized from the video, performing a photographing operation to obtain a photo containing the character action characteristics.
In step 202, the first in-vehicle camera may be any one of vehicle-mounted cameras installed inside the vehicle for capturing the conditions inside the vehicle, and is mainly used for continuously capturing video pictures of the conditions inside the vehicle in real time. The first in-vehicle camera may be disposed at any suitable location on the front screen, on the rear view mirror, under the rear view mirror, on the rear screen, or on the roof of the vehicle.
In step 204, the character motion characteristics include a character facial expression motion and/or a character limb motion, i.e., motion characteristics of the vehicle-related person, such as the driver and/or other members of the vehicle, appearing in the video frame captured by the first vehicle camera. Facial expression actions of the person such as smiling, blewing, tongue removal, etc., limb actions of the person such as biking, hugging, stretching the palm, etc.
Based on the solutions provided by the above embodiments, optionally, as shown in fig. 2, fig. 2 is a schematic flow chart of the step of recognizing the character motion characteristics according to the first embodiment of the present application.
The step 204 of performing character motion feature recognition on the video includes:
In the process of continuously shooting the video in real time by the camera in the first vehicle, the current frame image of the shot video is obtained, and a pre-trained motion recognition model is input, so that the recognition result of the current frame image can be obtained, and whether certain or certain character motion characteristics exist in the current frame image is judged.
The first motion recognition model can be obtained by training an intelligent neural network, and input training samples comprise a plurality of image samples with character motion characteristics and a plurality of image samples without character motion characteristics, so that the first motion recognition model is finally obtained through adaptive learning and convergence of the neural network.
As described above, the first in-vehicle camera continuously captures the video in real time, that is, the video is always being generated, and in this embodiment, the current frame image is also captured and acquired. Therefore, whether the person in the vehicle moves or not can be timely identified through the mode.
Based on the solutions provided by the above embodiments, optionally, as shown in fig. 3, fig. 3 is a schematic flow chart of a human motion feature recognition step according to a second embodiment of the present application.
The step 204 of performing character motion feature recognition on the video includes:
In this embodiment, the second motion recognition model is also obtained by training the intelligent neural network, and the input training samples include a plurality of image samples with specific human motion characteristics and a plurality of image samples without specific human motion characteristics, such as a special human motion characteristic of smiling, tongue regurgitation, hugging and so on, which are common emotions or motions suitable for photographing. Therefore, the second action recognition model is finally obtained through the self-adaptive learning and convergence of the neural network.
At this time, in the process of continuously shooting the video in real time by the first in-vehicle camera, a current multi-frame image of the shot video is obtained, wherein the current multi-frame image can be a subsequent shot multi-frame image, such as 2-4 frames of images, continuously collected after the fact that the action characteristic of a person exists in one currently obtained frame of image is identified. And inputting a pre-trained action recognition model to obtain a recognition result of the current multi-frame image so as to judge whether the action characteristic of the currently recognized person is a certain action. Such as tongue expectoration. Thus, the action of the vehicle member is judged through a sequence of images.
Optionally, before performing the character motion feature recognition on the video in step 204, the method further includes: the method comprises the steps of obtaining a sensitivity level for triggering recognition of the character action features, wherein the sensitivity level corresponds to the action amplitude of the character action features, and the higher the sensitivity level is, the larger the action amplitude of the character action features required for triggering the recognition is.
The first in-vehicle camera is used for shooting videos of the internal conditions of the vehicle normally, and the shooting operation is triggered based on the result of recognizing the action characteristics of people. In one embodiment, in order to meet the needs of the user more accurately, conditions for performing the photo operation may be set according to the user's pre-selection, such as a case where the user wants to take a snap when the adult in the vehicle has a smile of a human face, but the smile is a case of different motion amplitude sizes such as a smile, a grin and a large-mouth opening, and the like, and the user wants to take a photo when the user has a grin. Therefore, the standard of the sensitivity level of the trigger recognition operation can be divided according to the magnitude of the action amplitude, for example, the action amplitude of the smile is small, and the corresponding sensitivity level is low; the action amplitude of grinning is medium, the corresponding sensitivity level is medium, the action amplitude of the opening is maximum, and the corresponding sensitivity level is high. Accordingly, the motion recognition model capable of recognizing large-amplitude, medium-amplitude or small-amplitude motion correspondingly can be obtained by training based on the selected samples.
If the user wishes to perform a photographing operation when the smile of grinning is recognized, the medium sensitivity level may be selected in advance. In this way, when the human motion feature recognition is performed on the video, if the input frame image is recognized by using the motion recognition model with the recognizable medium amplitude, the frame image not including the medium amplitude motion is not recognized by the motion recognition model, and accordingly, the photographing operation in step 206 is not triggered. Only if the frame picture conforming to the medium-amplitude motion is detected by the motion recognition model, the photographing operation of step 206 is triggered. If it is a smiling action, the expression action of laughing or smiling is not recognized, and thus a photographing operation is not triggered. Whereas a medium-amplitude grin would be recognized and captured, and the resulting photograph would exhibit the grin facial expression.
That is, by acquiring the sensitivity level preset by the user, the magnitude of the motion amplitude that can trigger the recognition of the character motion feature can be determined in advance, so as to determine the corresponding character motion amplitude contained in the photo obtained after the photographing is performed.
Of course, the user may not pre-select a sensitivity level, but the system defaults to a sensitivity level. And based on the default sensitivity level, when the character action characteristics corresponding to the action amplitude are identified, triggering to execute the photographing operation to obtain the corresponding in-car photographed picture.
Based on the solution provided by the above embodiment, optionally, in step 206, when the character motion feature is identified from the video, the photographing operation is performed, and includes: when the character action characteristics are identified from the video, starting a customized photographing function, and executing a photographing operation by a second in-vehicle camera according to the customized photographing function; or when the character action characteristics are identified from the video, sending a photographing instruction to the first in-vehicle camera or the second in-vehicle camera so that the first in-vehicle camera or the second in-vehicle camera executes photographing operation according to the photographing instruction.
The customized photographing function has the photographing functions of processing operations such as automatic cutting, light supplementing, filter beautifying and the like, so that the requirements of users are met better. The second in-vehicle camera can be connected to a Central Processing Unit (CPU) in the vehicle-mounted intelligent network system through a wire and is used for executing photo acquisition corresponding to the customized photographing function. The second in-vehicle camera may be different from or the same as the first in-vehicle camera for shooting the in-vehicle video.
Or after the character action characteristics are identified, a photographing instruction is sent, and the camera in the vehicle executes photographing operation. Here, the in-vehicle camera that performs photographing may be a first in-vehicle camera or a second in-vehicle camera. After receiving the returned photo shot by the camera in the vehicle, the obtained photo containing the character action characteristics can be customized, including but not limited to processing operations such as automatic cutting, light supplement, filter beautification and the like.
When the camera in the vehicle performs photographing operation, 3-time continuous photographing or 5-time continuous photographing can be performed, and a Gif picture can be additionally generated so that a user can select an optimal snapshot.
In one embodiment, further comprising: and saving or sharing the photo to a social platform. Therefore, the social platform can be shared after the in-vehicle photographing is completed, and the automobile data recorder does not need to be copied to a computer or a mobile phone from a memory card or a manufacturer cloud platform. The operation steps are simple, and the user experience and the sharing desire are improved.
Next, the in-vehicle photographing processing method of the present application will be described with reference to an example of fig. 4, where fig. 4 is an example flow diagram of the in-vehicle photographing processing method of the embodiment of the present application.
As shown in fig. 4, the method comprises the following steps:
step 502: and starting an automatic snapshot mode.
And the automatic snapshot mode is started to identify the character action characteristics of the video shot by the camera in the vehicle so as to execute the shooting operation based on the identification result. Whether the automatic snapshot mode is started or not is manually started after the owner considers the privacy condition and agrees at a proper time.
Step 504: a trigger sensitivity level is selected.
The user selects trigger sensitivity levels, e.g., high, medium, and low sensitivity levels. As described above, the system may also default to a sensitivity level that is not selected by the user.
Step 506: whether a photographing instruction is detected.
Here, it is determined whether a character motion characteristic triggering a corresponding sensitivity level is recognized, for example, a facial expression motion or a limb motion is recognized.
Step 508: and performing 3 continuous beats or 5 continuous beats.
Step 510: an extra Gif format picture is generated.
Here, the above steps 508 to 510 are to perform the photographing operation according to the preset photographing setting mode.
Step 512: sending out an inquiry prompt for judging whether to store the photo corresponding to the photo, and if so, entering step 514; if not (N), the deletion is prompted to be finished.
Step 514: and sending a query prompt for whether to share the photo to the social platform, and if so, entering step 516.
Step 516: and executing one-key sharing operation based on the operation of the user, so that the corresponding snapshot is shared to the social platform selected by the user.
Step 518: and saving the photos to the local.
This application carries out personage's action characteristic discernment to video through the video of the relevant vehicle internal conditions of camera shooting in the real-time acquisition car, works as follow carry out the operation of shooing during discernment personage's action characteristic in the video, in order to obtain and contain the photo of personage's action characteristic, the mode that so utilizes personage's action characteristic discernment carries out automatic snapshot, reduces the influence that current artifical initiative was taken a picture and is caused the driver, improves the security that the vehicle was gone to can also become the person normal condition in the car and exchange, when interactive, can not miss the splendid moment.
When the automobile travels, if the driver and the passenger forget to take a picture in the automobile, a plurality of people cannot take a picture in a closed mode, the shooting angle is not suitable, or the expression is unnatural, the mode of automatic shooting through the character action characteristic recognition provided by the application can ensure that the driver can drive the automobile safely, and the passengers can communicate naturally to enjoy the life of the intelligent automobile. The application is a novel interactive mode, can bring brand-new interactive experience for the user, under the condition of guaranteeing driving safety, bring better for user service and experience, increase the hommization and the customer care degree of brand.
Optionally, an embodiment of the present application further provides an in-vehicle photographing processing system, as shown in fig. 5, fig. 5 is a schematic structural diagram of the in-vehicle photographing processing system according to the embodiment of the present application.
The in-vehicle photographing processing system 1000 comprises an in-vehicle camera 100, an intelligent networking system 200 and a customized photographing Application (APP)300, wherein the customized photographing application 300 is installed in the intelligent networking system 200.
The in-vehicle camera 100 is used for shooting videos related to the internal conditions of the vehicle in real time;
the intelligent internet system 200 is configured to obtain a video shot by the in-vehicle camera 100 in real time, perform character motion feature recognition on the video, and send a shooting instruction to the customized shooting application when character motion features are recognized from the video;
the customized photographing application 300 is configured to execute a customized function photographing operation according to the photographing instruction, and obtain a photo including the character motion characteristics.
The intelligent internet system 200 according to the embodiment of the present application can perform each process of implementing any one of the above embodiments of the in-vehicle photographing processing method, and can achieve the same technical effect, and is not described herein again to avoid repetition.
Optionally, an in-vehicle photographing processing device is further provided in the embodiment of the present application, and fig. 6 is a schematic structural diagram of the in-vehicle photographing processing device in the embodiment of the present application. As shown in fig. 6, the in-vehicle photographing processing method apparatus 2000 includes a memory 2200 and a processor 2400 connected to the memory 2200, where the memory 2200 stores a computer program that can be executed by the processor 2400, and when the computer program is executed by the processor, the computer program implements each process of any one of the above-mentioned in-vehicle photographing processing method embodiments, and can achieve the same technical effect, and is not repeated here to avoid repetition.
The embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of any one of the above-mentioned in-vehicle photographing processing method embodiments, and can achieve the same technical effect, and is not described herein again to avoid repetition. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An in-vehicle photographing processing method is characterized by comprising the following steps:
acquiring videos of relevant vehicle internal conditions shot by a first vehicle camera in real time;
performing character action feature recognition on the video;
and when the character action characteristics are recognized from the video, performing photographing operation to obtain a photo containing the character action characteristics.
2. The method of claim 1, wherein the character motion features comprise character facial expression motions and/or character limb motions.
3. The method of claim 1, wherein performing character motion feature recognition on the video comprises:
acquiring a current frame image of the video;
and inputting the current frame image into a preset first action recognition model to recognize whether the human action characteristics exist in the current frame image.
4. The method of claim 1, wherein performing character motion feature recognition on the video comprises:
acquiring a current multi-frame image of the video;
and inputting the current multi-frame image into a predetermined second motion recognition model to recognize whether a specific human motion characteristic exists in the current multi-frame image.
5. The method of claim 3 or 4, wherein prior to performing human motion feature recognition on the video, further comprising:
the method comprises the steps of obtaining a sensitivity level for triggering recognition of the character action features, wherein the sensitivity level corresponds to the action amplitude of the character action features, and the higher the sensitivity level is, the larger the action amplitude of the character action features required for triggering the recognition is.
6. The method of claim 1, wherein performing a photographing operation when the character motion feature is identified from the video comprises:
when the character action characteristics are identified from the video, starting a customized photographing function, and executing a photographing operation by a second in-vehicle camera according to the customized photographing function; or
When the character action characteristics are identified from the video, a photographing instruction is sent to the first in-vehicle camera or the second in-vehicle camera, so that the first in-vehicle camera or the second in-vehicle camera executes photographing operation according to the photographing instruction.
7. The method of claim 1, further comprising:
and saving or sharing the photo to a social platform.
8. An in-vehicle photographing processing system is characterized by comprising an in-vehicle camera, an intelligent internet system and a customized photographing application, wherein the customized photographing application is installed in the intelligent internet system,
the camera in the vehicle is used for shooting videos related to the internal conditions of the vehicle in real time;
the intelligent network system is used for acquiring videos shot by the camera in the vehicle in real time, identifying character action characteristics of the videos and sending a shooting instruction to the customized shooting application when the character action characteristics are identified from the videos;
and the customized photographing application is used for executing the photographing operation of the customized function according to the photographing instruction and obtaining the photo containing the character action characteristics.
9. The utility model provides a processing apparatus shoots in car which characterized in that includes: a memory and a processor electrically connected to the memory, the memory storing a computer program executable on the processor, the computer program, when executed by the processor, implementing the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113266975A (en) * | 2021-04-20 | 2021-08-17 | 华人运通(江苏)技术有限公司 | Vehicle-mounted refrigerator control method, device, equipment and storage medium |
| CN113923355A (en) * | 2021-09-30 | 2022-01-11 | 上海商汤临港智能科技有限公司 | Vehicle, image shooting method, device, equipment and storage medium |
| CN114845040A (en) * | 2021-07-08 | 2022-08-02 | 长城汽车股份有限公司 | Image processing method and device based on human-vehicle interaction, vehicle and storage medium |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010177990A (en) * | 2009-01-29 | 2010-08-12 | Nikon Corp | Digital camera |
| CN205524667U (en) * | 2016-02-01 | 2016-08-31 | 广东濠绅控股有限公司 | On -vehicle recorder and bicycle of making a video recording of bicycle |
| CN107610276A (en) * | 2017-10-18 | 2018-01-19 | 深圳市美特高电子科技有限公司 | The gesture of improved drive recorder is taken pictures and method for recording and system |
| CN108737729A (en) * | 2018-05-04 | 2018-11-02 | Oppo广东移动通信有限公司 | Automatic photographing method and device |
| CN109416733A (en) * | 2016-07-07 | 2019-03-01 | 哈曼国际工业有限公司 | Portable personalization |
| CN109922266A (en) * | 2019-03-29 | 2019-06-21 | 睿魔智能科技（深圳）有限公司 | Grasp shoot method and system, video camera and storage medium applied to video capture |
| CN209112092U (en) * | 2018-10-25 | 2019-07-16 | 浙江吉利汽车研究院有限公司 | Interior filming apparatus and automobile |
| CN110070058A (en) * | 2019-04-25 | 2019-07-30 | 信利光电股份有限公司 | A kind of vehicle-mounted gesture identifying device and system |
| CN210348570U (en) * | 2019-10-18 | 2020-04-17 | 本田汽车用品(广东)有限公司 | Intelligence vehicle event data recorder |
| KR102150967B1 (en) * | 2019-03-26 | 2020-09-02 | (주)헥스하이브 | Automotive security system capable of shooting in all directions |
-
2020
- 2020-11-27 CN CN202011352706.6A patent/CN112511746A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010177990A (en) * | 2009-01-29 | 2010-08-12 | Nikon Corp | Digital camera |
| CN205524667U (en) * | 2016-02-01 | 2016-08-31 | 广东濠绅控股有限公司 | On -vehicle recorder and bicycle of making a video recording of bicycle |
| CN109416733A (en) * | 2016-07-07 | 2019-03-01 | 哈曼国际工业有限公司 | Portable personalization |
| CN107610276A (en) * | 2017-10-18 | 2018-01-19 | 深圳市美特高电子科技有限公司 | The gesture of improved drive recorder is taken pictures and method for recording and system |
| CN108737729A (en) * | 2018-05-04 | 2018-11-02 | Oppo广东移动通信有限公司 | Automatic photographing method and device |
| CN209112092U (en) * | 2018-10-25 | 2019-07-16 | 浙江吉利汽车研究院有限公司 | Interior filming apparatus and automobile |
| KR102150967B1 (en) * | 2019-03-26 | 2020-09-02 | (주)헥스하이브 | Automotive security system capable of shooting in all directions |
| CN109922266A (en) * | 2019-03-29 | 2019-06-21 | 睿魔智能科技（深圳）有限公司 | Grasp shoot method and system, video camera and storage medium applied to video capture |
| CN110070058A (en) * | 2019-04-25 | 2019-07-30 | 信利光电股份有限公司 | A kind of vehicle-mounted gesture identifying device and system |
| CN210348570U (en) * | 2019-10-18 | 2020-04-17 | 本田汽车用品(广东)有限公司 | Intelligence vehicle event data recorder |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113266975A (en) * | 2021-04-20 | 2021-08-17 | 华人运通(江苏)技术有限公司 | Vehicle-mounted refrigerator control method, device, equipment and storage medium |
| CN114845040A (en) * | 2021-07-08 | 2022-08-02 | 长城汽车股份有限公司 | Image processing method and device based on human-vehicle interaction, vehicle and storage medium |
| CN113923355A (en) * | 2021-09-30 | 2022-01-11 | 上海商汤临港智能科技有限公司 | Vehicle, image shooting method, device, equipment and storage medium |
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Application publication date: 20210316 |