Name
Abstract | ||
|---|---|---|
A visually demanding driving environment, where elements surrounding a driver are constantly and rapidly changing, requires a driver to make spatially large head turns. Many existing state of the art vision based head pose algorithms, however, still have difficulties in continuously monitoring the head dynamics of a driver. This occurs because, from the perspective of a single camera, spatially large head turns induce self-occlusions of facial features, which are key elements in determining head pose. In this paper, we introduce a shape feature based multi-perspective framework for continuously monitoring the driver's head dynamics. The proposed approach utilizes a distributed camera setup to observe the driver over a wide range of head movements. Using head dynamics and a confidence measure based on symmetry of facial features, a particular perspective is chosen to provide the final head pose estimate. Our analysis on real world driving data shows promising results. |
Year | Venue | Keywords |
|---|---|---|
2013 | 2013 16TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS - (ITSC) | head,pose estimation,algorithms |
Field | DocType | ISSN |
Computer vision,Simulation,Head movements,Advanced driver assistance systems,Pose,Vision based,Large head,Artificial intelligence,Engineering,Feature based | Conference | 2153-0009 |
Citations | PageRank | References |
6 | 0.62 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sujitha Martin | 1 | 177 | 12.72 |
| Ashish Tawari | 2 | 219 | 16.07 |
| Mohan M. Trivedi | 3 | 6564 | 475.50 |