Combining Features for Shape and Motion Trajectory of Video Objects for Efficient Content Based Video Retrieval

Abstract

This paper proposes a system for content based video retrieval based on shape and motion features of the video object. We have used Curvature scale space for shape representation and Polynomial curve fitting for trajectory representation and retrieval. The shape representation is invariant to translation, rotation and scaling and robust with respect to noise. Trajectory matching incorporates visual distance, velocity dissimilarity and size dissimilarity for retrieval. The cost of matching two video objects is based on shape and motion features, to retrieve similar video shots. We have tested our system on standard synthetic databases. We have also tested our system on real world databases. Experimental results have shown good performance.