Nonrigid Motion Analysis Based on Dynamic Refinement of Finite Element Models
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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In this paper we propose new methods for human tissue motion analysis from range image sequences using the nonlinear Finite Element Method (FEM). The approach combines range data, mechanics of human tissues, and dynamics of their motion using nonlinear finite element models. We are able to evaluate the changes in strain distribution over time. Given images at two time instances and their corresponding features, we use FEM to synthesize intermediate images not only of the displacement fields, but also of the strains of the underlying tissues. This results in a physically-based framework for motion and strain analysis. The results from the skin elasticity experiments show promise of detecting differences in elasticity between normal and abnormal tissue. The results from the hand motion experiments indicate the level of strain that could be causing Repetitive Stress Injury (RSI). Our work demonstrates the possibility of accurate quantitative analysis and force recovery in range image sequences containing nonrigid objects.