Name
Abstract | ||
|---|---|---|
In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects' abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragments-based tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation. |
Year | Venue | Field |
|---|---|---|
2015 | EAI Endorsed Trans. Cognitive Communications | Computer vision,Computer science,Particle filter,Video tracking,Particle filtering algorithm,Artificial intelligence |
DocType | Volume | Issue |
Journal | 1 | 3 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Sun | 1 | 1 | 1.04 |
| Zhi Liu | 2 | 23 | 14.28 |
| Haixia Zhang | 3 | 366 | 54.02 |