4 March 2015 Driver alertness detection using Google Glasses
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Abstract
This paper proposes an intelligent vehicle system (ITS) to monitor the driver driving behavior. Based on the first-person vision (FPV) technology (or Google glasses), our system can detect the vehicle exterior/interior scene from driver’s viewpoint and estimate driver gazing direction. First, we use “bag of words” image classification approach by applying FAST and BRIEF feature descriptor in the dataset. Then, we use vocabulary dictionary to encode an input image as feature vectors. Finally, we apply SVM classifier to identify whether the input image is vehicle interior scene or not to monitor the driver driving attention. Second, we find the correspondence between the images of the Google glasses and the camera mounted on the wind shield of the vehicle to estimate the gazing direction of the driver. In the experiments, we illustrate the effectiveness of our system.
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Kuang-Yu Liu, Kuang-Yu Liu, Chung-Lin Huang, Chung-Lin Huang, } "Driver alertness detection using Google Glasses", Proc. SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015, 94070B (4 March 2015); doi: 10.1117/12.2076577; https://doi.org/10.1117/12.2076577
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