Goal: Real-Time Segmentation via Graph Cut Goal: Real-Time Segmentation via Graph Cut

Abstract

The detection of moving objects is a crucial part of driver assistance systems. This paper tackles this issue using computer vision. Two approaches are investigated, monocular and stereoscopic. The base principals and implementational issues are discussed and detailed, high- lighting areas of concern. In both cases, the detection is based on motion analysis of individually tracked image points (optical ow). The monoc- ular approach relies solely on the optical ow, where as the stereoscopic approach also takes stereo depth information into account. In both ap- proaches the motion analysis provides a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric the points are segmented into objects by employing the globally op- timal graph cut algorithm. These approaches are then compared and contrasted using real-world vehicle image sequences.