Vision-Based Infotainment User Determination by Hand Recognition for Driver Assistance

We present a novel real-time computer-vision system that robustly discriminates which of the front-row seat occupants is accessing the infotainment controls. The knowledge of who is the user--that is, driver, passenger, or no one--can alleviate driver distraction and maximize the passenger infotainment experience. The system captures visible and near-infrared images of the frontrow seat area in the vehicle. The algorithm uses a modified histogram-of-oriented-gradients feature descriptor to represent the image area over the infotainment controls and a support vector machine (SVM) and median filtering over time to classify each image to one of the three classes with 97.9% average correct classification rate. This rate was achieved over a wide range of illumination conditions, human subjects, and times of day. With an offset of 5 pixels in any direction, the rate could still be maintained at better than 85%. This approach represents an alternative to detecting and tracking the hand moveme...

• Type: Journal
• Year: 2010
• Where: TITS
• Authors: Shinko Y. Cheng, Mohan M. Trivedi
• Keywords: Classification Rates, Education, Infotainment, Passenger Infotainment Experience, TITS 2010