Publication Type
Conference Proceeding Article
Publication Date
8-2004
Abstract
This paper proposes a unified approach for initializing, detecting and tracking of multiple moving objects. Object initialization is achieved through novel seed selection which is adaptively activated, depending on the quality of tracking, to select the best possible frames along the temporal direction for object detection. EM algorithm is then employed to robustly segment and detect multiple objects in a selected frame. Each detected object is represented by an appearance-based model and mean shift tracking procedure is adopted to rapidly and effectively track the target objects.
Discipline
Computer Sciences | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, 2004 August 23-26
Volume
2
First Page
744
Last Page
747
ISBN
0769521282
Identifier
10.1109/ICPR.2004.1334366
Publisher
IEEE
City or Country
Cambridge
Citation
PAN, Zailiang and NGO, Chong-wah.
Novel seed selection for multiple objects detection and tracking. (2004). Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, 2004 August 23-26. 2, 744-747.
Available at: https://ink.library.smu.edu.sg/sis_research/6555
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
