In this paper, we construct a new class of deformable models using a new family of biorthogonal wavelets, named generalized Hermite Distributed Approximating Functional (g-HDAF) Wavelets. The scaling functions of this new family are symmetric and the corresponding wavelets optimize their smoothness for a given number of vanishing moments. In addition, we embed these multiresolution deformable models to the physics-based deformable model framework and use them for fitting 3D range data. We have performed a number of experiments with both synthetic and real data with very encouraging results.
CITATION STYLE
Kakadiaris, I. A., Papadakis, E., Shen, L., Kouri, D., & Hoffman, D. (2002). g-HDAF multiresolution deformable models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2492, pp. 21–31). Springer Verlag. https://doi.org/10.1007/3-540-36138-3_2
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