Abstract
Accurate rigid and non-rigid tracking of faces is a challenging task in computer vision. Recently, appearance-based 3D face tracking methods have been proposed. These methods can successfully tackle the image variability and drift problems. However, they may fail to provide accurate out-of-plane face motions since they are not very sensitive to out-of-plane motion variations. In this paper, we present a framework for fast and accurate 3D face and facial action tracking. Our proposed framework retains the strengths of both appearance and 3D data-based trackers. We combine an adaptive appearance model with an online stereo-based 3D model. We provide experiments and performance evaluation which show the feasibility and usefulness of the proposed approach.
This work was supported by the MEC project TIN2005-09026 and The Ramón y Cajal Program.
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Dornaika, F., Sappa, A.D. (2006). Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo-Based 3D Models. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_62
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DOI: https://doi.org/10.1007/11864349_62
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