Abstract
A driving environment that is changing constantly and rapidly, demands a driver to make large head turns. Drivers head movements are strong indicators of drivers focus on the road. In this paper a vision based algorithm is presented to estimate the driver head pose. Determining the head pose using vision based algorithms is a non-invasive method in intelligent driver assistance systems. Many existing state of the art vision based head pose algorithms have difficulties in monitoring the driver head movements. This is because in single camera perspective spatially large head turns disturb the facial features which are necessary to determine the head pose. A distributed camera framework and the use of Constrained Local Model algorithm for head pose tracking is presented. The proposed approach monitors the driver head over wide range of movements.
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