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Robust Non-Rigid Object Tracking Using Point Distribution Models

This paper presents a robust approach to non-rigid object tracking in video sequences. The object to track is described by a 2-dimensional point distribution model whose landmarks correspond to interest points that are automatically extracted from the object and described by their geometrical position and their local appearance. The approach is novel in that we describe the appearance locally instead of using the raw texture information. This provides a natural way to robustly handle partial occlusions. A second contribution is that we present a method that allows to learn the model automatically. Our algorithms have been successfully tested on several video streams taken from soccer games and video surveillance footage. They have been implemented with the aim of achieving near real-time performance.