Motion segmentation using feature selection and subspace method based on shape space

Motion segmentation using feature correspondences can be regarded as a combinatorial problem. A motion segmentation algorithm using feature selection and subspace method is proposed to solve the combinatorial problem. Feature selection is carried out as computation of a basis of the linear space that represents the shape of objects. Features can be selected from “each” object “without segmentation information” by keeping the correspondence of basis vectors to features. Only four or less features of each object are used; the combination in segmentation is reduced by feature selection. Thus the combinatorial problem can be solved without optimization. The remaining features in selection are classified using the subspace method based on the segmentation result of selected features. Experiments are done to consider the usefulness of the proposed method