Sparse motion segmentation using multiple six-point consistencies

Details Sparse motion segmentation using multiple six-point consistencies Sparse motion segmentation using multiple six-point consistencies

2010-12-09

arxiv.org/abs/1012.2138v2

VECTaR workshop (with ACCV) 2010

Computer Science

Computer Vision and Pattern Recognition

Scientific paper

We present a method for segmenting an arbitrary number of moving objects in image sequences using the geometry of 6 points in 2D to infer motion consistency. The method has been evaluated on the Hopkins 155 database and surpasses current state-of-the-art methods such as SSC, both in terms of overall performance on two and three motions but also in terms of maximum errors. The method works by finding initial clusters in the spatial domain, and then classifying each remaining point as belonging to the cluster that minimizes a motion consistency score. In contrast to most other motion segmentation methods that are based on an affine camera model, the proposed method is fully projective.

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