A Robust and Efficient Motion Segmentation Based on Orthogonal Projection Matrix of Shape Space

A novel algorithm for motion segmentation is proposed. The algorithm uses the fact that shape of an object with homogeneous motion is represented as 4 dimensional linear space. Thus motion segmentation is done as the decomposition of shape space of multiple objects into a set of 4 dimensional subspace. The decomposition is realized using the discriminant analysis of orthogonal projection matrix of shape space. Since only discriminant analysis of 1D data is needed, this analysis is quite simple. The algorithm based on the analysis is robust for data with noise and outliers, because the analysis can extract useful information for motion segmentation while rejecting useless one. The implementation results show that the proposed method is robust and efficient enough to do online task for real scenes.