Moving Object Segmentation Using Optical Flow and Depth Information

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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

Jens Klappstein, Tobi Vaudrey, Clemens Rabe, Andre

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Driver Assistance Systems | Optical ﬂow | Optimal Graph-cut Algorithm | PSIVT 2009 |

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Added	27 Jul 2010
Updated	27 Jul 2010
Type	Conference
Year	2009
Where	PSIVT
Authors	Jens Klappstein, Tobi Vaudrey, Clemens Rabe, Andreas Wedel, Reinhard Klette

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Moving Object Segmentation Using Optical Flow and Depth Information

Driver Assistance Systems | Optical ﬂow | Optimal Graph-cut Algorithm | PSIVT 2009 |

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