Name
Abstract | ||
|---|---|---|
This paper introduces a multiple human objects tracking system to detect and track multiple objects in the crowded scene in which occlusions occur. Our method assign each pixel to different human object based on its relative distance to that object and the corresponding color model. If no occlusion, we easily track each object independently based on each segmented object region and optical flow. With occlusion, we analyze the color distribution of the occlusion group to differentiate each object in the group. By calculating the distances between objects, we can determine whether an object is separated from the occlusion group and to be tracked individually afterwards |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICPR.2006.841 | ICPR (3) |
Keywords | Field | DocType |
color distribution,object region segmentation,multiple human objects tracking,image segmentation,occlusions,multiple human object,corresponding color model,relative distance,multiple object,crowded scene,crowded scenes,image sequences,object detection,different human object,optical flow,occlusion group,segmented object region,image colour analysis,color model,object tracking | Deep-sky object,Object detection,Computer vision,Pattern recognition,Computer science,Segmentation-based object categorization,Tracking system,Image segmentation,Color model,Artificial intelligence,Pixel,Optical flow | Conference |
Volume | ISSN | ISBN |
3 | 1051-4651 | 0-7695-2521-0 |
Citations | PageRank | References |
6 | 0.49 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yao-Te Tsai | 1 | 6 | 0.49 |
| Huang-Chia Shih | 2 | 187 | 21.98 |
| Chung-Lin Huang | 3 | 540 | 37.61 |