Robust face tracking by integration of two separate trackers: Skin color and facial shape
SCIE
SCOPUS
- Title
- Robust face tracking by integration of two separate trackers: Skin color and facial shape
- Authors
- Hyung-Soo Lee; Kim, DJ
- Date Issued
- 2007-11
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Abstract
- This paper proposes a robust face tracking method based on the condensation algorithm that uses skin color and facial shape as observation measures. Two trackers are used for robust tracking: one tracks the skin color regions and the other tracks the facial shape regions. The two trackers are coupled using an importance sampling technique, where the skin color density obtained from the skin color tracker is used as the importance function to generate samples for the shape tracker. The samples of the skin color tracker within the chosen shape region are updated with higher weights. Also, an adaptive color model is used to avoid the effect of illumination change in the skin color tracker. The proposed face tracker performs more robustly than either the skin-color-based tracker or the facial shape-based tracker, given the presence of background clutter and/or illumination changes. (c) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
- Keywords
- face tracking; skin color; facial shape; condensation; importance sampling
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/23244
- DOI
- 10.1016/j.patcog.2007.03.003
- ISSN
- 0031-3203
- Article Type
- Article
- Citation
- PATTERN RECOGNITION, vol. 40, no. 11, page. 3225 - 3235, 2007-11
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