Article ID Journal Published Year Pages File Type
527617 Image and Vision Computing 2007 12 Pages PDF
Abstract

Parameters used in physical models for nonrigid and articulated motion analysis are often not known with high precision. It has been recognized that commonly used assumptions about the parameters may have adverse effect on modeling quality. In this paper, we present an efficient sensitivity analysis method to assess the impact of those assumptions by examining the model's spatial response to parameter perturbation. Numerical experiments with a synthetic model and skin tissues show that: (1) normalized sensitivity distribution can help determine the relative importance of different parameters; (2) dimensional sensitivity is useful in the assessment of a particular parameter assumption; and (3) models are more sensitive at the locations of property discontinuity (heterogeneity). The formulation of the proposed sensitivity analysis method is general and can be applied to assessment of other types of assumptions, such as those related to nonlinearity and anisotropy.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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