Name
Abstract | ||
|---|---|---|
Tracking of moving-objects in image sequences is needed for several video processing applications such as content-based coding, object oriented compression, object recognition and more recently for video object plane extraction in MPEG-4 coding. Tracking is a natural follow-up of motion-based segmentation It is a fast and efficient method to achieve coherent motion segments along the temporal axis. Segmenting out moving objects for each and every frame in a video sequence is a computationally expensive approach. Thus, for better performance, semi-automatic segmentation is an acceptable compromise as automatic segmentation approaches [1] rely heavily on prior assumptions. In semi-automatic segmentation approaches, motion-segmentation is performed only on the initial frame and the moving object is tracked in subsequent frames using tracking algorithms.In this paper, a new model for object tracking is proposed, where the image features - edges, intensity pattern, object motion and initial keyed-in contour (by the user) form the prior and likelihood model of a Markov Random Field (MRF) model. Iterated Conditional Mode (ICM) is used for the minimisation of the global energy for the MRF model. The motion segment for each frame is initialised using the segment information from the previous frame. For the initial frame, the motion segment is obtained by manually keying in the object contour.The motion-segments obtained using the proposed model are coherent and accurate. Experimental results on tracking using the proposed algorithm for different sequences - Bream, Alexis and Claire are presented in this paper. The results obtained are accurate and can be used for a variety of applications including MPEG-4 Video Object Plane (VOP) extraction. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1117/12.411824 | VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2001 |
Keywords | DocType | Volume |
content-based coding, object tracking, Markov Random Field (MRF), Video Object Plane (VOP), MPEG-40 | Conference | 4310 |
ISSN | Citations | PageRank |
0277-786X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Parimal Aswani | 1 | 11 | 1.10 |
| K. K. Wong | 2 | 43 | 10.57 |
| Man N. Chong | 3 | 0 | 0.34 |