An Energy Minimization Approach to 3D Non-Rigid Deformable Surface Estimation Using RGBD Data

TL;DR

This paper introduces an energy minimization algorithm using RGBD data to estimate the shape of non-rigid objects without relying on predefined features, effective even on textureless surfaces.

Contribution

The method enables non-rigid surface estimation from RGBD images without predetermined features, handling unmodified and textureless objects through a 3D nonlinear energy minimization framework.

Findings

Successfully estimates configurations of dynamic non-rigid objects

Operates without predefined features or correspondences

Effective on textureless objects with no prior feature matching

Abstract

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.