CN113792599A - Verification method and verification device for fatigue driving early warning system - Google Patents
Verification method and verification device for fatigue driving early warning system Download PDFInfo
- Publication number
- CN113792599A CN113792599A CN202110915675.9A CN202110915675A CN113792599A CN 113792599 A CN113792599 A CN 113792599A CN 202110915675 A CN202110915675 A CN 202110915675A CN 113792599 A CN113792599 A CN 113792599A
- Authority
- CN
- China
- Prior art keywords
- fatigue driving
- warning system
- early warning
- picture
- recognition
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000012795 verification Methods 0.000 title abstract description 25
- 230000009471 action Effects 0.000 claims abstract description 24
- 238000012360 testing method Methods 0.000 claims abstract description 19
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000009661 fatigue test Methods 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 13
- 238000004590 computer program Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 8
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Images
Landscapes
- Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
Abstract
The invention provides a verification method and a verification system of a fatigue driving early warning system, wherein video playback test software is integrated in the fatigue driving early warning system, driving actions of a driver under different test scenes are recorded by the video playback test software, recorded pictures are input into a recognition algorithm of the fatigue driving early warning system, a fatigue driving recognition result is output, the recognition result is compared with an actual result, the recognition accuracy of the recognition algorithm of the fatigue driving early warning system is further obtained, and the recognition algorithm of the fatigue driving early warning system is continuously improved according to the recognition accuracy, so that the recognition algorithm of the fatigue driving early warning system is optimal.
Description
Technical Field
The invention relates to the field of automobile driving, in particular to a verification method and a verification device of a fatigue driving early warning system.
Background
When a vehicle-mounted fatigue driving early warning system is developed, a fatigue driving recognition algorithm is frequently modified, the recognition accuracy of a new algorithm is frequently required to be tested, the recognition accuracy of the algorithm is mainly calculated manually at present, and the vehicle-mounted fatigue driving early warning system is low in efficiency and inaccurate.
Disclosure of Invention
The invention provides a verification method and a verification device of a fatigue driving early warning system, aiming at the technical problems in the prior art.
According to a first aspect of the present invention, there is provided a method for verifying a fatigue driving warning system, comprising: installing a fatigue driving early warning system on a vehicle, wherein video playback test software is integrated in the fatigue driving early warning system; starting video playback test software, recording a video stream of corresponding driving actions of a driver in driving under different test scenes through a camera, and storing each frame of picture in the video stream; inputting each frame of picture into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result; and judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
On the basis of the technical scheme, the invention can be improved as follows.
Optionally, the video playback test software is started, and the video stream of the corresponding driving action made by the driver in driving under different test scenes is recorded by the camera, including: starting video playback test software of the fatigue driving early warning system, and recording video streams of corresponding fatigue driving actions made by a driver in driving; and saving each frame of picture in the video stream as a jpg picture, and saving.
Optionally, the video playback test software for starting the fatigue driving early warning system to record the video stream of the corresponding fatigue driving action made by the driver during driving includes: and acquiring YUV images of each frame of camera video stream through a linux V4L2 video acquisition interface of the fatigue driving early warning system, wherein the fatigue driving early warning system uses a linux system.
Optionally, the acquiring, by a linux V4L2 video acquisition interface of the fatigue driving early warning system, a YUV image of each frame of a camera video stream includes: opening a fatigue driving early warning system of the/dev/video 0 based on an open function, setting an acquisition mode to a capture mode based on an ioctl function, and setting an acquisition frame rate and resolution; and setting the output format to be a YUV format based on ioctl.
Optionally, the storing each frame of picture in the video stream as a jpg picture, and storing the jpg picture includes: and converting the YUV image into a jpg picture based on a video conversion interface cvtColor in the opencv, and calling an opencv interface imwrite to store the picture in a hard disk.
Optionally, the inputting each frame of picture into the recognition algorithm of the fatigue driving early warning system to obtain the recognition result of fatigue driving includes: starting video playback testing software of the fatigue driving early warning system, reading each jpg picture by the video playback testing software through an opencv interface immed, and converting each jpg picture into a corresponding YUV image through a picture-to-YUV interface cvtColor in opencv; and inputting each YUV image into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result, wherein the fatigue driving recognition result is fatigue driving or non-fatigue driving.
Optionally, the inputting each YUV image into a recognition algorithm of the fatigue driving early warning system to obtain a fatigue driving recognition result, and then further comprising: and marking the fatigue driving identification result corresponding to each YUV image on the YUV image.
Optionally, the determining, according to the fatigue driving recognition result and the actual result corresponding to each frame of picture, the recognition accuracy of the recognition algorithm of the fatigue driving early warning system, and then further comprising: and improving the recognition algorithm of the fatigue driving early warning system based on the recognition accuracy of the recognition algorithm of the fatigue driving early warning system, and continuously verifying the recognition accuracy of the recognition algorithm of the fatigue driving early warning system until the recognition accuracy reaches a set accuracy.
According to a second aspect of the present invention, there is provided a verification apparatus for a fatigue driving warning system, comprising: the recording module is used for starting video playback test software, recording a video stream of corresponding driving actions made by a driver in driving under different test scenes, and storing each frame of picture in the video stream; the acquisition module is used for inputting each frame of picture into a recognition algorithm of the fatigue driving early warning system to acquire a fatigue driving recognition result; and the judging module is used for judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
According to a third aspect of the present invention, there is provided an electronic device comprising a memory, a processor for implementing the steps of the method of verifying a fatigue driving warning system when executing a computer management-like program stored in the memory.
According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having stored thereon a computer management-like program, which when executed by a processor, implements the steps of the verification method of the fatigue driving warning system.
The invention provides a verification method and a verification device of a fatigue driving early warning system, which integrate video playback test software in the fatigue driving early warning system, utilize the video playback test software to record the driving actions of a driver under different test scenes, input recorded pictures into an identification algorithm of the fatigue driving early warning system, output a fatigue driving identification result, compare the identification result with an actual result, further obtain the identification accuracy of the identification algorithm of the fatigue driving early warning system, and continuously improve the identification algorithm of the fatigue driving early warning system according to the identification accuracy so that the identification algorithm of the fatigue driving early warning system is optimal.
Drawings
Fig. 1 is a flowchart of a verification method of a fatigue driving warning system according to the present invention;
FIG. 2 is a flow chart of video stream image capture;
FIG. 3 is a flowchart of recognition algorithm accuracy acquisition for a fatigue driving warning system;
fig. 4 is a schematic structural diagram of a verification device of a fatigue driving early warning system provided by the invention;
FIG. 5 is a schematic diagram of a hardware structure of a possible electronic device provided in the present invention;
fig. 6 is a schematic diagram of a hardware structure of a possible computer-readable storage medium according to the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Fig. 1 is a flowchart of a verification method of a fatigue driving warning system provided in the present invention, as shown in fig. 1, the method includes: 101. installing a fatigue driving early warning system on a vehicle, wherein video playback test software is integrated in the fatigue driving early warning system; 102. starting video playback test software, recording a video stream of corresponding driving actions of a driver in driving under different test scenes through a camera, and storing each frame of picture in the video stream; 103. inputting each frame of picture into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result; 104. and judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
It can be understood that, based on the defects in the background art, the embodiment of the invention provides a video playback test software implementation method of a fatigue driving early warning system, which is used for rapidly testing the recognition rate of an algorithm when the fatigue driving early warning system is developed, so that the recognition rate of the algorithm of the fatigue driving early warning system is improved, and the testing labor and time are reduced.
The fatigue driving early warning system is installed at the installation position of the vehicle during final mass production, and the fatigue driving early warning system is integrated with video playback test software. And starting video playback test software, recording the driving action of the driver in different test scenes, acquiring video streams, and storing each picture of the video streams. And inputting each stored picture into a recognition algorithm of the fatigue driving early warning system, acquiring a fatigue driving recognition result corresponding to each picture, and judging the recognition accuracy of the fatigue driving early warning system recognition algorithm on the pictures according to the fatigue driving recognition result and the actual result corresponding to each picture.
When the fatigue driving early warning system is installed on a vehicle, the video stream of the camera of the fatigue driving early warning system is acquired and stored as a picture, after a new algorithm of the fatigue driving early warning system is changed, the stored picture is processed by the algorithm, the algorithm identification rate is judged according to whether the algorithm is successfully identified, and then the algorithm is continuously updated to improve the algorithm identification rate.
In a possible embodiment, the starting of the video playback test software records, through a camera, a video stream of a corresponding driving action performed by a driver during driving in different test scenes, and includes: starting video playback test software of the fatigue driving early warning system, and recording video streams of corresponding fatigue driving actions made by a driver in driving; and saving each frame of picture in the video stream as a jpg picture, and saving.
It can be understood that after the fatigue driving early warning system and the video playback test software are installed on the vehicle, video recording is carried out on fatigue driving actions of the driver under different test scenes. Specifically, the vehicle is started, video playback test software of the fatigue driving early warning system is started, a driver makes fatigue driving actions, and video recording is carried out on the fatigue driving actions of the driver.
The steps of collecting video streams and saving the video streams as pictures can be seen in fig. 2, and specifically include the following steps:
step 21: and (3) starting a program, wherein the fatigue driving early warning system uses a linux system, and a linux V4L2 video acquisition interface is used for acquiring YUV data of each frame of the video stream of the camera. Firstly, opening a device of "/dev/video 0" by using an open function, then setting an acquisition mode to a capture mode by using an ioctl function, setting an acquisition frame rate and resolution, and then setting an output format to a YUV format by using ioctl.
Step 22: and allocating a video buffer area to be 3 frames, and starting to circularly acquire video frames.
Step 23: and converting the YUV data into a jpg picture by using a video conversion interface cvtColor in opencv, and calling an opencv interface imwrite to store the picture in a hard disk.
Step 24: and after the storage is finished, inserting the usb device, mounting the USB flash disk, and copying the data into the USB flash disk.
Step 25: and repeating the steps 21-22-23, converting the video streams in various scenes into jpg pictures and saving the jpg pictures to a USB flash drive.
In a possible embodiment mode, inputting each frame of picture into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result, including: starting video playback testing software of the fatigue driving early warning system, reading each jpg picture by the video playback testing software through an opencv interface immed, and converting each jpg picture into a corresponding YUV image through a picture-to-YUV interface cvtColor in opencv; and inputting each YUV image into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result, wherein the fatigue driving recognition result is fatigue driving or non-fatigue driving.
It can be understood that, the recording of the fatigue driving actions of the driver under different test scenes according to the foregoing steps S21 to S25, and the following description of the recognition accuracy of the recognition algorithm for obtaining the fatigue driving warning system, referring to fig. 3, mainly includes the following steps:
step 31: and inserting a USB flash disk with pictures into the fatigue driving early warning system device.
Step 32: and starting video playback testing software of the fatigue driving early warning system, reading a jpg picture from a u disk by using an opencv interface immed by the software, and converting the jpg picture into a YUV image by using a picture-to-YUV interface cvtColor in the opencv.
Step 33: and calling a fatigue driving recognition algorithm, transmitting the YUV image to the algorithm, and obtaining a fatigue driving recognition result after the algorithm processing is finished.
Step 34: drawing the fatigue driving recognition result on the YUV image, and outputting the YUV image to a screen by using a V4L2 interface.
Step 35: and judging whether the recognition algorithm correctly recognizes the YUV image according to the fatigue recognition result and the actual result of the YUV image through the recognition algorithm of the fatigue driving recognition system, and further calculating whether the recognition result of the YUV image by the recognition algorithm of the fatigue driving system is correct.
Step 36: and after the algorithm is modified, repeating the steps 31-32-33-34-35, and continuously verifying the identification accuracy of the identification algorithm of the fatigue driving system. And continuously improving the recognition algorithm of the fatigue driving early warning system, and continuously verifying the recognition accuracy of the recognition algorithm of the fatigue driving early warning system until the recognition accuracy reaches a set accuracy.
Fig. 4 is a structural diagram of a verification device of a fatigue driving warning system according to an embodiment of the present invention, and as shown in fig. 4, the verification device of the fatigue driving warning system includes a recording module 41, an obtaining module 42, and a determining module 43, where:
the recording module 41 is configured to start video playback test software, record a video stream of a corresponding driving action performed by a driver during driving in different test scenes, and store each frame of picture in the video stream; the obtaining module 42 is configured to input each frame of picture into a recognition algorithm of the fatigue driving early warning system to obtain a fatigue driving recognition result; and the judging module 43 is configured to judge the recognition accuracy of the recognition algorithm of the fatigue driving early warning system according to the fatigue driving recognition result and the actual result corresponding to each frame of picture.
It can be understood that the verification device of the fatigue driving early warning system provided by the present invention corresponds to the verification method of the fatigue driving early warning system provided by the foregoing embodiments, and the related technical features of the verification device of the fatigue driving early warning system may refer to the related technical features of the verification method of the fatigue driving early warning system, and are not described herein again.
Referring to fig. 5, fig. 5 is a schematic view of an embodiment of an electronic device according to an embodiment of the invention. As shown in fig. 5, an embodiment of the present invention provides an electronic device 500, which includes a memory 510, a processor 520, and a computer program 511 stored in the memory 510 and executable on the processor 520, wherein the processor 520 executes the computer program 511 to implement the following steps: starting video playback test software, recording a video stream of corresponding driving actions of a driver in driving under different test scenes through a camera, and storing each frame of picture in the video stream; inputting each frame of picture into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result; and judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
Referring to fig. 6, fig. 6 is a schematic diagram of an embodiment of a computer-readable storage medium according to the present invention. As shown in fig. 6, the present embodiment provides a computer-readable storage medium 600 having a computer program 611 stored thereon, the computer program 611, when executed by a processor, implementing the steps of: starting video playback test software, recording a video stream of corresponding driving actions of a driver in driving under different test scenes through a camera, and storing each frame of picture in the video stream; inputting each frame of picture into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result; and judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
The embodiment of the invention provides a verification method and a verification device of a fatigue driving early warning system, which integrate video playback test software in the fatigue driving early warning system, utilize the video playback test software to record driving actions of a driver under different test scenes, input recorded pictures into an identification algorithm of the fatigue driving early warning system, output a fatigue driving identification result, compare the identification result with an actual result, further obtain the identification accuracy of the identification algorithm of the fatigue driving early warning system, and continuously improve the identification algorithm of the fatigue driving early warning system according to the identification accuracy so that the identification algorithm of the fatigue driving early warning system is optimal.
It should be noted that, in the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to relevant descriptions of other embodiments for parts that are not described in detail in a certain embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A method for verifying a fatigue driving warning system is characterized by comprising the following steps:
installing a fatigue driving early warning system on a vehicle, wherein video playback test software is integrated in the fatigue driving early warning system;
starting video playback test software, recording a video stream of corresponding driving actions of a driver in driving under different test scenes through a camera, and storing each frame of picture in the video stream;
inputting each frame of picture into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result;
and judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
2. The method for verifying the fatigue timely warning system according to claim 1, wherein the step of starting video playback test software to record video streams of corresponding driving actions of a driver in driving under different test scenes by a camera comprises the following steps:
starting video playback test software of the fatigue driving early warning system, and recording video streams of corresponding fatigue driving actions made by a driver in driving;
and saving each frame of picture in the video stream as a jpg picture, and saving.
3. The method for verifying the fatigue driving warning system according to claim 2, wherein the step of starting the video playback test software of the fatigue driving warning system to record the video stream of the corresponding fatigue driving action made by the driver during driving comprises:
and acquiring YUV images of each frame of camera video stream through a linux V4L2 video acquisition interface of the fatigue driving early warning system, wherein the fatigue driving early warning system uses a linux system.
4. The method for verifying the fatigue driving warning system according to claim 3, wherein the capturing each frame of YUV image of the video stream of the camera via the linux V4L2 video capture interface of the fatigue driving warning system comprises:
opening a fatigue driving early warning system of the/dev/video 0 based on an open function, setting an acquisition mode to a capture mode based on an ioctl function, and setting an acquisition frame rate and resolution;
and setting the output format to be a YUV format based on ioctl.
5. The method for verifying the fatigue driving warning system according to claim 4, wherein the saving each frame of picture in the video stream as a jpg picture and saving comprises:
and converting the YUV image into a jpg picture based on a video conversion interface cvtColor in the opencv, and calling an opencv interface imwrite to store the picture in a hard disk.
6. The method for verifying the fatigue driving warning system according to claim 2 or 5, wherein the step of inputting each frame of picture into the recognition algorithm of the fatigue driving warning system to obtain the recognition result of fatigue driving comprises:
starting video playback testing software of the fatigue driving early warning system, reading each jpg picture by the video playback testing software through an opencv interface immed, and converting each jpg picture into a corresponding YUV image through a picture-to-YUV interface cvtColor in opencv;
and inputting each YUV image into a recognition algorithm of a fatigue driving early warning system to obtain a fatigue driving recognition result, wherein the fatigue driving recognition result is fatigue driving or non-fatigue driving.
7. The method for verifying the fatigue driving warning system according to claim 6, wherein the step of inputting each YUV image into the recognition algorithm of the fatigue driving warning system to obtain the recognition result of fatigue driving further comprises the following steps:
and marking the fatigue driving identification result corresponding to each YUV image on the YUV image.
8. The method for verifying the fatigue driving warning system according to claim 1, wherein the determining of the recognition accuracy of the recognition algorithm of the fatigue driving warning system according to the recognition result and the actual result of the fatigue driving corresponding to each frame of the picture further comprises:
and improving the recognition algorithm of the fatigue driving early warning system based on the recognition accuracy of the recognition algorithm of the fatigue driving early warning system, and continuously verifying the recognition accuracy of the recognition algorithm of the fatigue driving early warning system until the recognition accuracy reaches a set accuracy.
9. The utility model provides a fatigue test drives early warning system's verifying attachment which characterized in that includes:
the recording module is used for starting video playback test software, recording a video stream of corresponding driving actions made by a driver in driving under different test scenes, and storing each frame of picture in the video stream;
the acquisition module is used for inputting each frame of picture into a recognition algorithm of the fatigue driving early warning system to acquire a fatigue driving recognition result;
and the judging module is used for judging the identification accuracy of the identification algorithm of the fatigue driving early warning system according to the fatigue driving identification result and the actual result corresponding to each frame of picture.
10. A computer-readable storage medium, on which a computer management-like program is stored, which, when executed by a processor, carries out the steps of the method of verifying a fatigue driving warning system according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110915675.9A CN113792599A (en) | 2021-08-10 | 2021-08-10 | Verification method and verification device for fatigue driving early warning system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110915675.9A CN113792599A (en) | 2021-08-10 | 2021-08-10 | Verification method and verification device for fatigue driving early warning system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113792599A true CN113792599A (en) | 2021-12-14 |
Family
ID=78875862
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110915675.9A Pending CN113792599A (en) | 2021-08-10 | 2021-08-10 | Verification method and verification device for fatigue driving early warning system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113792599A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104182338A (en) * | 2014-08-19 | 2014-12-03 | 苏州清研微视电子科技有限公司 | Fatigue driving early warning product detection accuracy test method |
| CN110393531A (en) * | 2019-05-23 | 2019-11-01 | 重庆大学 | A kind of method for detecting fatigue driving and system based on smart machine |
| CN110532925A (en) * | 2019-08-22 | 2019-12-03 | 西安电子科技大学 | Driver Fatigue Detection based on space-time diagram convolutional network |
| CN110796207A (en) * | 2019-11-08 | 2020-02-14 | 中南大学 | Fatigue driving detection method and system |
| CN111753674A (en) * | 2020-06-05 | 2020-10-09 | 广东海洋大学 | Fatigue driving detection and identification method based on deep learning |
| CN111968353A (en) * | 2020-07-31 | 2020-11-20 | 东风商用车有限公司 | Testing method and system of fatigue driving early warning system |
-
2021
- 2021-08-10 CN CN202110915675.9A patent/CN113792599A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104182338A (en) * | 2014-08-19 | 2014-12-03 | 苏州清研微视电子科技有限公司 | Fatigue driving early warning product detection accuracy test method |
| CN110393531A (en) * | 2019-05-23 | 2019-11-01 | 重庆大学 | A kind of method for detecting fatigue driving and system based on smart machine |
| CN110532925A (en) * | 2019-08-22 | 2019-12-03 | 西安电子科技大学 | Driver Fatigue Detection based on space-time diagram convolutional network |
| CN110796207A (en) * | 2019-11-08 | 2020-02-14 | 中南大学 | Fatigue driving detection method and system |
| CN111753674A (en) * | 2020-06-05 | 2020-10-09 | 广东海洋大学 | Fatigue driving detection and identification method based on deep learning |
| CN111968353A (en) * | 2020-07-31 | 2020-11-20 | 东风商用车有限公司 | Testing method and system of fatigue driving early warning system |
Non-Patent Citations (1)
| Title |
|---|
| 阿迪蒂尼•夏尔马 等: "《机器学习:使用OpenCV、Python和scikit-learn进行智能图像处理 原书第2版》", 31 March 2010, 西安电子科技大学出版社, pages: 364 - 206 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20060285750A1 (en) | Imaging apparatus, processing method of the apparatus and program making computer execute the method | |
| EP2128868A3 (en) | Image pickup apparatus, image pickup method, playback control apparatus, playback control method, and program | |
| CN101098403A (en) | Imaging apparatus and computer readable recording medium | |
| CN101047792A (en) | Image processing device, image processing method and imaging device | |
| CN106292625B (en) | Vehicle fault online detection system and method | |
| CN102148931A (en) | Image sensing device | |
| WO2019024488A1 (en) | Vehicle damage assessment method, electronic device and computer readable storage medium | |
| CN101056362A (en) | Image display control apparatus, method of controlling the same, and control program therefor | |
| US7777800B2 (en) | Digital still camera and image processing system | |
| CN110443814B (en) | Loss assessment method, device, equipment and storage medium for vehicle | |
| CN112307842A (en) | Video identification system and method for matching of train operation monitoring record files | |
| US8233057B2 (en) | Apparatus and method for image capturing | |
| US8243154B2 (en) | Image processing apparatus, digital camera, and recording medium | |
| CN113792599A (en) | Verification method and verification device for fatigue driving early warning system | |
| CN112215222A (en) | License plate recognition method, device, equipment and storage medium | |
| CN116437139B (en) | Classroom video recording method, device, storage medium and equipment | |
| US20230096532A1 (en) | Machine learning system, learning data collection method and storage medium | |
| US20120075495A1 (en) | Electronic camera | |
| CN110324549B (en) | Video recording method, device and equipment | |
| CN110704459A (en) | Method, medium and system for cleaning zombie vehicle data of parking lot | |
| US20210400192A1 (en) | Image processing apparatus, image processing method, and storage medium | |
| CN114120206A (en) | Vehicle end target detection method and device based on mobile end | |
| JP2010183253A (en) | Information display device and information display program | |
| CN111553408B (en) | Automatic test method for video recognition software | |
| CN113792600A (en) | Video frame extraction method and system based on deep learning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |