Separation of multiple objects in motion images by clustering

A method is presented for estimating the number of rigid objects moving independently and separating the feature points tracked on a motion image into individual objects by clustering. In the method, feature points are firstly mapped into a low dimensional space suitable for grouping them into each object. In this low dimensional space, clusters are extracted sequentially by a graph spectral method. The number of clusters i.e. objects can be estimated on the basis of the variation in the cohesiveness of extracted clusters. We show by numerical experiments that the present method is robust to moderate measurement noises and distortion by perspective projection.