Moving Object Segmentation Using Optical Flow and Depth Information

Authors:
Jens Klappstein;Tobi Vaudrey;Clemens Rabe;Andreas Wedel;Reinhard Klette
Affiliations:
Environment Perception Group, Daimler AG, Sindelfingen, Germany;enpeda.. Project, The University of Auckland, New Zealand;Environment Perception Group, Daimler AG, Sindelfingen, Germany;Environment Perception Group, Daimler AG, Sindelfingen, Germany;enpeda.. Project, The University of Auckland, New Zealand
Venue:
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Year:
2009

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Abstract

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.