Vehicle tracking from disparate views

Most approaches to vehicle tracking have adopted a single calibrated camera for the task, which leads to an under-conditioned problem. We present a surveillance system for on-line vehicle tracking based on two cameras and structure from motion (SfM). Our surveillance system starts by tracking feature points. A novel matching scheme is proposed that allows a subset of feature points to be corresponded across disparate views. Based on the reconstructed subset, the full set of feature points are reconstructed in 3D and segmented into different vehicles by solving a multiple labeling problem.