Tracking feature points in time-varying images using an opportunistic selection approach

摘要

In tracking of feature points in time-varying images, one major issue is to identify the feature points at different times that represent the same physical object point. This process is often called the ‘correspondence problem’ and is an important research issue in both motion analysis and stereopsis. This paper describes a new approach toward the tracking of feature points in time-varying images by reasoning about the trajectories of feature points. The advantage of this approach is that the solution can be computed efficiently and the algorithm can potentially be supported by multiple processor computer. This approach is tested extensively on synthesized data. The statistics on the experiments strongly suggests the generality and the robustness of the approach.