Name
Abstract | ||
|---|---|---|
Estimating people’s head pose is an important problem, for which many solutions have been proposed. Most existing solutions are based on the use of a single camera and assume that the head is confined in a relatively small region of space. If we need to estimate unintrusively the head pose of persons in a large environment, however, we need to use several cameras to cover the monitored area. In this work, we propose a novel solution to the multi-camera head pose estimation problem that exploits the additional amount of information that provides multi-camera configurations. Our approach uses the probability estimates produced by multi-class support vector machines to calculate the probability distribution of the head pose. The distributions produced by the cameras are fused, resulting in a more precise estimate than the one provided individually. We report experimental results that confirm that the fused distribution provides higher accuracy than the individual classifiers and a high robustness against errors. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s00138-012-0410-z | Mach. Vis. Appl. |
Keywords | DocType | Volume |
Head pose,Multiple views,Support vector machines,People tracking | Journal | 23 |
Issue | ISSN | Citations |
3 | 0932-8092 | 9 |
PageRank | References | Authors |
0.52 | 33 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Muñoz-Salinas | 1 | 353 | 25.03 |
| E. Yeguas-Bolivar | 2 | 52 | 2.80 |
| Alessandro Saffiotti | 3 | 2755 | 284.17 |
| R. Medina-Carnicer | 4 | 417 | 24.80 |