Name
Abstract | ||
|---|---|---|
Multiple-target tracking represents a challenging question in uncontrolled scenarios. Due to high-level applications, such as behavioral analysis, the need of a robust tracking system is high. In a multiple tracking scenario it is necessary to consider and resolve occlusions, as well as formations and splitting of object groups. In this work, a method based in a hierarchical architecture for multiple tracking is proposed to deal with these matters. Background subtraction, blob detection, low-level tracking, collision detection and high-level appearance tracking is used to avoid occlusion and grouping problems. Experimental results show promising results in tracking management, grouping, splitting, occlusion events, while remains invariant to illumination changes. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21593-3_42 | ICIAR |
Keywords | Field | DocType |
multiple tracking scenario,grouping problem,low-level tracking,multiple tracking,adaptive filter,robust tracking system,multiple-target tracking,high-level application,collision detection,blob detection,high-level appearance tracking | Background subtraction,Computer vision,Collision detection,Pattern recognition,Computer science,Tracking system,Video tracking,Behavioral analysis,Artificial intelligence,Invariant (mathematics),Adaptive filter,Blob detection | Conference |
Volume | ISSN | Citations |
6753 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brais Cancela | 1 | 66 | 9.19 |
| M Ortega | 2 | 235 | 37.13 |
| Manuel G. Penedo | 3 | 185 | 35.91 |
| A. Fernández | 4 | 0 | 0.34 |