Pedestrian Detection for Intelligent Vehicles Based on Active Contour Models and Stereo Vision

Recently, the focus of safety systems for intelligent vehicles has been on researching and developing Advanced Driver Assistance Systems (ADAS). Most efforts have been concentrated at the driver, not taking into account the protection of the most vulnerable road users. This paper describes a pedestrian detection algorithm based on stereo vision. The use of visual information is a promising approach to cope with the different appearances of pedestrians and changes of illumination in cluttered environments. Active contour models are used to detect and track people from the images taken by an on-board vision system, performing contour extraction in sequential frames.