An Energy Minimization Approach to 3D Non-Rigid Deformable Surface Estimation Using RGBD Data
This addresses the challenge of 3D non-rigid surface estimation for applications like robotics or computer vision, but it appears incremental as it builds on energy minimization techniques.
The paper tackles the problem of estimating the 3D configuration of non-rigid objects using RGBD data, achieving results that demonstrate the method's ability to handle textureless objects without correspondences.
We propose an algorithm that uses energy mini- mization to estimate the current configuration of a non-rigid object. Our approach utilizes an RGBD image to calculate corresponding SURF features, depth, and boundary informa- tion. We do not use predetermined features, thus enabling our system to operate on unmodified objects. Our approach relies on a 3D nonlinear energy minimization framework to solve for the configuration using a semi-implicit scheme. Results show various scenarios of dynamic posters and shirts in different configurations to illustrate the performance of the method. In particular, we show that our method is able to estimate the configuration of a textureless nonrigid object with no correspondences available.