Real-Time Descriptorless Feature Tracking

This paper presents a simple and efficient estimator of long-term sparse optical flow. It is supported by a novel approach to feature tracking, essentially based on global coherence of local movements. Expensive invariant appearance descriptors are not required: the locations of salient points in successive frames provide enough information to create a large number of accurate and stable tracking histories which remain alive for significantly long times. Hence, wide-baseline matching can be achieved both in extremely regular scenes and in cases in which corresponding points are photometrically very different. Our experiments show that this method is able to robustly maintain in real time hundreds Of trajectories in long video sequences using a standard computer.