Progressive Finite Newton Approach To Real-time Nonrigid Surface Detection

Detecting nonrigid surfaces is an interesting research problem for computer vision and image analysis. One important challenge of nonrigid surface detection is how to register a nonrigid surface mesh having a large number of free deformation parameters. This is particularly significant for detecting nonrigid surfaces from noisy observations. Nonrigid surface detection is usually regarded as a robust parameter estimation problem, which is typically solved iteratively from a good initialization in order to avoid local minima. In this paper, we propose a novel progressive finite Newton optimization scheme for the nonrigid surface detection problem, which is reduced to only solving a set of linear equations. The key of our approach is to formulate the nonrigid surface detection as an unconstrained quadratic optimization problem which has a closed-form solution for a given set of observations. Moreover, we employ a progressive active-set selection scheme, which takes advantage of the rank ...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Jianke Zhu, Michael R. Lyu
• Keywords: Computer Vision, CVPR 2007, Nonrigid Surface Detection, Nonrigid Surface Mesh, Parameter Estimation Problem, Quadratic Optimization Problem, Surface Detection Problem