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Independent motion detection in 3D scenes

机译:3D场景中的独立运动检测

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摘要

This paper presents an algorithmic approach to the problem of detecting independently moving objects in 3D scenes that are viewed under camera motion. There are two fundamental constraints that can be exploited for the problem: 1) two/multiview camera motion constraint (for instance, the epipolar/trilinear constraint) and 2) shape constancy constraint. Previous approaches to the problem either use only partial constraints, or rely on dense correspondences or flow. We employ both the fundamental constraints in an algorithm that does not demand a priori availability of correspondences or flow. Our approach uses the plane-plus-parallax decomposition to enforce the two constraints. It is also demonstrated that for a class of scenes, called sparse 3D scenes in which genuine parallax and independent motions may be confounded, how the plane-plus-parallax decomposition allows progressive introduction, and verification of the fundamental constraints. Results of the algorithm on some difficult sparse 3D scenes are promising.
机译:本文提出了一种算法方法,用于检测在摄像机运动下观看的3D场景中独立移动的对象。有两个基本约束可用于解决该问题:1)两个/多视图摄像机运动约束(例如,对极/三线性约束)和2)形状恒定约束。解决该问题的先前方法要么仅使用部分约束,要么依赖密集的对应关系或流程。我们在不需要先验对应关系或流程可用性的算法中采用了两个基本约束。我们的方法使用平面加视差分解来强制执行两个约束。还证明了对于一类称为稀疏3D场景的场景(其中可能混淆真正的视差和独立运动),平面加视差分解如何允许逐步引入,并验证了基本约束。该算法在一些困难的稀疏3D场景上的结果很有希望。

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