Name
Abstract | ||
|---|---|---|
Tracking moving objects is one of the most important but problematic features of motion analysis and understanding. The Kalman filter (KF) has commonly been used for estimation and prediction of the target position in succeeding frames. In this paper, we propose a novel and efficient method of tracking, which performs well even when the target takes a sudden turn during its motion. The proposed method arbitrates between KF and Optical flow (OF) to improve the tracking performance. Our system utilizes a laser to measure the distance to the nearest obstacle and an infrared camera to find the target. The relative data is then fused with the Arbitrate OFKF filter to perform real-time tracking. Experimental results show our suggested approach is very effective and reliable for estimating and tracking moving objects. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.image.2011.06.005 | Sig. Proc.: Image Comm. |
Keywords | Field | DocType |
target position,arbitrate ofkf filter,tracking performance,kalman filter,efficient method,optical flow,mobile agent,kalman filter arbitration,motion analysis,human tracking,real-time tracking,mobile robot | Obstacle,Computer vision,Computer science,Mobile agent,Tracking system,Kalman filter,Arbitration,Artificial intelligence,Motion analysis,Optical flow,Mobile robot | Journal |
Volume | Issue | ISSN |
27 | 1 | 0923-5965 |
Citations | PageRank | References |
18 | 0.72 | 39 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuichi Motai | 1 | 230 | 24.68 |
| Sumit Kumar Jha | 2 | 257 | 32.68 |
| Daniel Kruse | 3 | 21 | 1.57 |