A Matching and Tracking Strategy for Independently Moving Objects

We present a robust and inherently parallel strategy for tracking "corner" features on independently moving (and possibly non-rigid) objects. The system operates over long, monocular image sequences and comprises two main parts. A matcher performs two-frame correspondence based on spatial proximity and similarity in local image structure, while a (racier maintains an image trajectory (and predictor) for every feature. The use of low-level features ensures an opportunistic and widely applicable algorithm. Moreover, the system copes with noisy data, predictor failure, and occlusion and disocclusion of scene structure. Motion and scene analysis modules can then be built onto this framework. The algorithm is aimed at applications with small inter-frame motion, such as videoconferencing.