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Abstract
This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of shape and texture information. With the shape and texture information at the feature points alone, we can achieve only an approximation to the deformation required. In such an under-determined condition, we find an optimal solution using a simple least square minimization method. As experimental results, we show well-reconstructed 2D faces even from a small number of feature points.
To whom all correspondence should be addressed. This research was supported by Creative Research Initiatives of the Ministry of Science and Technology, Korea.
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References
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Authors and Affiliations
Center for Artificial Vision Research, Korea University, Anam-dong, Seongbuk-ku, Seoul, 136-701, Korea
Bon-Woo Hwang & Seong-Whan Lee
Max-Planck-Institute for Biological Cybernetics, Spemannstr. 38, 72076, Tuebingen, Germany
Volker Blanz & Thomas Vetter
- Bon-Woo Hwang
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- Volker Blanz
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- Thomas Vetter
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- Seong-Whan Lee
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Editors and Affiliations
Center for Artificial Vision Research, Korea University, Anam-dong, Seongbuk-ku, Seoul, 136-701, Korea
Seong-Whan Lee
Max-Planck-Institute for Biological Cybernetics, Spemannstr. 38, 72076, Tübingen, Germany
Heinrich H. Bülthoff
Department of Brain and Cognitive Sciences Artificial Intelligence Laboratory, E25-218, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA, 02142, USA
Tomaso Poggio
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Hwang, BW., Blanz, V., Vetter, T., Lee, SW. (2000). Face Reconstruction Using a Small Set of Feature Points. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_30
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