Name
Title | ||
|---|---|---|
Markov random field modeled level sets method for object tracking with moving cameras |
Abstract | ||
|---|---|---|
Object tracking using active contours has attracted increasing interest in recent years due to acquisition of effective shape descriptions. In this paper, an object tracking method based on level sets using moving cameras is proposed. We develop an automatic contour initialization method based on optical flow detection. A Markov Random Field (MRF)-like model measuring the correlations between neighboring pixels is added to improve the general region-based level sets speed model. The experimental results on several real video sequences show that our method successfully tracks objects despite object scale changes, motion blur, background disturbance, and gets smoother and more accurate results than the current region-based method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76386-4_79 | ACCV (1) |
Keywords | Field | DocType |
markov random field,speed model,object tracking,automatic contour initialization method,current region-based method,object tracking method,object scale change,general region-based level,accurate result,active contour,level set,level set method,optical flow | Active contour model,Computer vision,Pattern recognition,Markov random field,Computer science,Motion blur,Level set,Video tracking,Artificial intelligence,Pixel,Initialization,Optical flow | Conference |
Volume | ISSN | ISBN |
4843 | 0302-9743 | 3-540-76385-6 |
Citations | PageRank | References |
6 | 0.56 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xue Zhou | 1 | 194 | 11.81 |
| Weiming Hu | 2 | 16 | 1.49 |
| Ying Chen | 3 | 6 | 0.56 |
| Wei Hu | 4 | 111 | 4.77 |