Real-time vision-based infotainment user determination for driver assistance

Knowledge of driver body pose can be used in many applications. In this paper, we develop and evaluate a novel real-time computer vision algorithm to robustly discriminate which of the front-row seat occupants is accessing the infotainment controls. The knowledge of user type can alleviate driver distraction and maximize passenger infotainment experience. The system consists of a visible and near-infrared imaging device observing the front-row seat area in the vehicle. Using histogram-of-oriented-gradients to describe the image area over the controls, a support-vector-machine was shown to be able to provide 96.8% average correct classification rate. This approach represents an alternative of detecting and tracking the hand movements and then classifying the hands into the respective classes.

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