Head tracking using video analytics

A robust, efficient video analytic tool is presented for detection and estimation of driver´s head position and orientation in the SHRP 2 NDS dataset. It is shown that by exploiting the temporal correlations between successive frames in a video, challenging conditions such as lighting variations, and lower resolutions, may be mitigated effectively. The Viola-Jones frontal face detector provides initial results. Then, statistical inference methods for spurious faces elimination and missing driver´s head detection are developed. Preliminary results show marked performance enhancement due to the proposed method.