Name
Abstract | ||
|---|---|---|
In this paper we address the problem of detection and tracking of pedestrians in complex scenarios. The inclusion of prior knowledge is more and more crucial in scene analysis to guarantee flexibility and robustness, necessary to have reliability in complex scenes. We aim to combine image processing methods with behavioral models of pedestrian dynamics, calibrated on real data. We introduce Discrete Choice Models (DCM) for pedestrian behavior and we discuss their integration in a detection and tracking context. The obtained results show how it is possible to combine both methodologies to improve the performances of such systems in complex sequences. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/s11263-005-4797-0 | International Journal of Computer Vision |
Keywords | Field | DocType |
Image Processing,Artificial Intelligence,Pattern Recognition,Computer Vision,Prior Knowledge | Computer vision,Pedestrian,Scene analysis,Computer science,Image processing,Robustness (computer science),Discrete choice,Artificial intelligence,Prior probability,Machine learning | Journal |
Volume | Issue | ISSN |
69 | 2 | 0920-5691 |
Citations | PageRank | References |
57 | 4.15 | 30 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gianluca Antonini | 1 | 192 | 13.67 |
| Santiago Venegas-Martinez | 2 | 57 | 4.82 |
| Michel Bierlaire | 3 | 273 | 26.07 |
| Jean Philippe Thiran | 4 | 77 | 6.74 |