Epipolar Curve Tracking in 3-D

Vehicle tracking in video sequences is typically carried out by matching 2-d views (images or features) of the vehicle from one frame to the next. These views are adapted by gradual changes in 2-d image transforms between frames. This approach can work well for sequences where the vehicle projection is not highly perspective and 3-d vehicle orientation with respect to the camera varies slowly. In this paper, vehicle tracking is studied under conditions that violate these assumptions. Tracking is carried out on high-definition videos sequences of vehicles that pass near the camera, causing severe perspective distortion. Perspective effects are accounted for by tracking edge curves on the vehicle and reconstructing them in 3-d, using structure from motion on adjacent frames. The result is segmentation of the vehicle from the background and recovery of its geometry and motion in 3-d.