Estimation of Composite Object and Camera Image Motion

An approach for estimating composite independent object and camera image motions is proposed. The approach employs spatio-temporal flow models learned through observing typical movements of the object, to decompose image motion into independent object and camera motions. The spatiotemporal flow models of the object motion are represented as a set of orthogonal flow bases that are learned using principal component analysis of instantaneous flow measurements from a stationary camera. These models are then employed in scenes with a moving camera to extract motion trajectories relative to those learned. The performance of the algorithm is demonstrated on several image sequences of rigid and articulated bodies in motion. 1 Introduction In recent years there has been increased interest in tracking and estimation of rigid and non-rigid object motion. Most approaches focused on tracking dynamic objects viewed from a stationary camera. In this paper we address the tracking and estimation of ob..