Efficient Multiple Independent Motion Segmentation from an Active Platform by Utilizing Modified RANSAC

Y. Xie and J. Ohya (Japan)

Keywords

Motion segmentation, modified RANSAC

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.

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