Multiscale combination of physically-based registration and deformation modeling

被引:0
|
作者
Tsap, LV [1 ]
Goldgof, DB [1 ]
Sarkar, S [1 ]
机构
[1] Univ Calif Lawrence Livermore Natl Lab, Ctr Appl Sci Comp, Livermore, CA 94551 USA
关键词
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we present a novel multiscale approach to recovery of nonrigid motion from sequences of registered intensity and range images. The main idea of our approach is that a finite element (FEM) model can naturally handle both registration and deformation modeling using a single model-driving strategy. The method includes a multiscale iterative algorithm based on analysis of the undirected Hausdorff distance to recover correspondences. The method is evaluated with respect to speed, accuracy, and noise sensitivity. Advantages of the proposed approach are demonstrated using man-made elastic materials and human skin motion. Experiments with regular grid features are used for performance comparison with a conventional approach (separate snakes and FEM models). it is shown that the new method does not require a grid and can adapt the model to available object features.
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页码:422 / 429
页数:8
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