Driver fatigue detecting method based on head gestures and eye movement
A driver fatigue and head posture technology, applied in the field of human-computer interaction, can solve driver fatigue and other problems, and achieve the effect of unconstrained detection of driver fatigue
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Embodiment 1
[0041] Such as figure 1 As shown, a driver fatigue detection method based on head posture and eye movement includes the following steps:
[0042] Step 1, acquiring an image sequence through a non-invasive image acquisition unit;
[0043] The face image acquisition unit is a camera set near the monitoring screen observed by the user, and is used to capture the user's face area. The user does not need to wear any auxiliary acquisition device (non-invasive), and the image used by the user in real time is collected through the camera, and converted It is a 256-level grayscale image.
[0044] The camera lens of the present invention is provided with an infrared filter, which can filter out the visible light band and retain the infrared band. The camera photosensitive element CCD or CMOS can be sensitive to the infrared band. Near the camera lens, an array of infrared LED light sources is arranged in a ring shape. According to the needs of the real environment, the brightness of...
Embodiment 2
[0050] In the embodiment of the present invention, although only one camera and one infrared LED light source are needed to complete image sampling, in order to obtain higher image signal quality, a multi-light source and multi-camera system can be used for division of labor and matching. Such as Image 6 As shown, it is another embodiment of the non-intrusive image acquisition unit. This embodiment provides a solution. The camera 1 is equipped with an infrared LED light source for shooting a wide scene and capturing a human face; the camera 2 and the camera 3 are used for shooting High-definition images of the eye area, and infrared LED light sources are installed in the upper left and upper right corners of the interactive screen.
[0051]Step 2. Based on the image sequence, in each frame of the image sequence, detect the face feature point image information and the eye region image information;
[0052] Step 3. Based on the feature points of the face in the image, analyze ...
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