Toward Smart Cars with Computer Vision for Integrated Driver and Road Scene Monitoring


Integration of the Lane Tracker and faceLAB



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Integration of the Lane Tracker and faceLAB



Combining the gaze direction captured by FaceLAB and the parameterised lane model determined by the lane tracker, we can track the visual behaviour of the driver relative to the road. Calculating the intercept of the eye gaze vectors with the road plane will determine whether the person is looking at the road, parallel with the road, to the right of the road or to the left of the road. Additionally, the visual scan patterns of the driver can be recorded with emphasis on fixation points and saccade movements to different regions in the scene. Figure 4 shows the segmentation of the driver visual attention areas for the experiments.

Figure 4

Results

A series of experiments were conducted to test the integrated system in different driving environments:

Preliminary results are shown in Figure 3 of two different scenarios. Outer city driving with high curvature roads and highway driving. The results showed that drivers have different focus of attention patterns for roads that have different types of curvature. It is possible to discriminate between highway driving and right, left curvature roads by analysing the histogram of behaviour of the driver’s visual attention.




The full paper will present the experimental results of the lane tracking system with an analysis of the particle filter and cue fusion algorithms used. Additionally, results from the integrated driver monitoring and lane tracking system will be presented focusing on the driver's visual behaviour with respect to viewing the road.

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