| Paper: | WP-P3.10 |
| Session: | Video Object Segmentation and Tracking III / Video Shot/Scene Segmentation |
| Time: | Wednesday, September 19, 14:30 - 17:10 |
| Presentation: |
Poster
|
| Title: |
EPIPOLAR CURVE TRACKING IN 3-D |
| Authors: |
Matthew Leotta; Brown University | | |
| | Joseph Mundy; Brown University | | |
| Abstract: |
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. |
