Name
Abstract | ||
|---|---|---|
In this paper, we address the problem of face tracking across illumination changes and occlusions. The method is based on leveraging the strengths of both Adaboost to deal with clutter and the image based parametric illumination model proposed by Kale and Jaynes. We show that a simple non-linear transformation of the Adaboost score multiplied with the illumination compensated likelihood leads to a fast robust tracking paradigm. We demonstrate the ability of our method to detect occlusions at the same time ensuring that mis-assignments between the occluder and the occluded does not occur. We present experimental results of our method on low resolution surveillance indoor and outdoor videos using an off the shelf DSP. We also demonstrate the power of the parametric illumination model for pose constrained face recognition when matching across known illumination conditions. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICASSP.2009.4959695 | Taipei |
Keywords | Field | DocType |
face recognition,lighting,pose estimation,realistic images,video surveillance,Adaboost score,face tracking,illumination changes,illumination compensated likelihood,nonlinear transformation,occlusions,parametric illumination model,pose constrained face recognition,real-life illumination conditions,resolution surveillance videos,robust tracking paradigm,shelf DSP,Face recognition,Surveillance,Tracking | Facial recognition system,Computer vision,AdaBoost,Pattern recognition,Computer science,Clutter,Pose,Robustness (computer science),Parametric statistics,Artificial intelligence,Face detection,Facial motion capture | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4244-2354-5 | 978-1-4244-2354-5 | 2 |
PageRank | References | Authors |
0.48 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rahul Thota | 1 | 2 | 0.48 |
| Archana Kalyansundar | 2 | 2 | 0.48 |
| Amit Kale | 3 | 708 | 48.47 |