Moving Object Segmentation Using Optical Flow and Depth Information

This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are comparatively evaluated using real-world vehicle image sequences. Key words: motion detection, optical flow, stereo, segmentation

• Type: Conference
• Year: 2009
• Where: PSIVT
• Authors: Jens Klappstein, Tobi Vaudrey, Clemens Rabe, Andreas Wedel, Reinhard Klette
• Keywords: Driver Assistance Systems, Optical flow, Optimal Graph-cut Algorithm, PSIVT 2009