Efficient multiple independent motion segmentation from an active platform by utilizing modified RANSAC

Authors:
Yingdi Xie;Jun Ohya
Affiliations:
Waseda University, Honjo City, Saitama Prefecture, Japan;Waseda University, Honjo City, Saitama Prefecture, Japan
Venue:
GVE '07 Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering
Year:
2007

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Abstract

In this paper, an efficient approach to segmentation of different independent motion areas from a moving platform is described. This approach is implemented on a stereo vision system, depth information could be computed by matching feature points between stereo images. For two consecutive frames, ego-motion is estimated from the optical flows, including depth information belonging to the background, which has a larger space distribution comparing to those of independent moving objects. In order to distinguish different motion areas, we proposed a modified version of RANSAC mechanism, which could handle the problem of multiple model extraction in a noisy environment.