Robust face tracking by integration of two separate trackers: Skin color and facial shape

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 couple...

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Bibliographic Details
Published in:Pattern recognition 2007-11, Vol.40 (11), p.3225-3235
Main Authors: Lee, Hyung-Soo, Kim, Daijin
Format: Article
Language:English
Subjects:
Applied sciences
Condensation
Exact sciences and technology
Face tracking
Facial shape
Importance sampling
Information, signal and communications theory
Pattern recognition
Signal processing
Skin color
Telecommunications and information theory
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Summary: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.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2007.03.003