Abstract
This paper summarizes our research efforts towards the development of a physics-based modeling framework that addresses the difficult problems of segmentation, shape and motion estimation in a uniform way. The framework is based on the sophisticated integration of mathematical techniques from geometry, physics and mechanics, with special emphasis on the design of algorithms with close to real-time performance. We demonstrate the usefulness of this framework in experiments involving image and range data, as well as in biomedical applications.
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Metaxas, D. (1995). A physics-based framework for segmentation, shape and motion estimation. In: Hebert, M., Ponce, J., Boult, T., Gross, A. (eds) Object Representation in Computer Vision. ORCV 1994. Lecture Notes in Computer Science, vol 994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60477-4_17
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DOI: https://doi.org/10.1007/3-540-60477-4_17
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