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EFFICIENT MULTIPLE INDEPENDENT MOTION SEGMENTATION FROM AN ACTIVE PLATFORM BY UTILIZING MODIFIED RANSAC

机译:利用改进的RANSAC从活动平台进行有效的多个独立运动分段

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摘要

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.
机译:在本文中,描述了一种从移动平台分割不同独立运动区域的有效方法。这种方法是在立体视觉系统上实现的,可以通过在立体图像之间匹配特征点来计算深度信息。对于两个连续的帧,根据包括属于背景的深度信息的光流来估计自我运动,与独立运动物体的空间分布相比,其具有更大的空间分布。为了区分不同的运动区域,我们提出了一种改进的RANSAC机制,可以解决嘈杂环境中的多模型提取问题。

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