Abstract
We demonstrate a method to automatically extract spatio-temporal descriptions of human faces from synchronized and calibrated multi-view sequences. The head is modeled by a time-varying multi-resolution subdivision surface that is fitted to the observed person using spatio-temporal multi-view stereo information, as well as contour constraints. The stereo data is utilized by computing the normalized correlation between corresponding spatio-temporal image trajectories of surface patches, while the contour information is determined using incremental background subtraction. We globally optimize the shape of the spatio-temporal surface in a coarse-to-fine manner using the multiresolution structure of the subdivision mesh. The method presented incorporates the available image information in a unified framework and automatically reconstructs accurate spatio-temporal representations of complex non-rigidly moving objects.
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Fig. 2. Results of 3D Structure and Motion Flow EstimationAuthor information
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Neumann, J., Aloimonos, Y. (2001). Spatio-temporal Analysis of Human Faces Using Multi-Resolution Subdivision Surfaces. In: Radig, B., Florczyk, S. (eds) Pattern Recognition. DAGM 2001. Lecture Notes in Computer Science, vol 2191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45404-7_9
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DOI: https://doi.org/10.1007/3-540-45404-7_9
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