Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
529586 | Image and Vision Computing | 2006 | 12 Pages |
Abstract
This paper presents methods for tracking moving objects in an outdoor environment. A robust tracking is achieved using feature fusion and multiple cameras. The proposed method integrates spatial position, shape and color information to track object blobs. The trajectories obtained from individual cameras are incorporated by an extended Kalman filter (EKF) to resolve object occlusion. Our results show that integrating simple features makes the tracking effective and that EKF improves the tracking accuracy when long-term or temporary occlusion occurs. The tracked objects are successfully classified into three categories: single person, people group, or vehicle.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Quming Zhou, J.K. Aggarwal,