Simultaneous Shape and Pose Adaption of Articulated Models Using Linear Optimization

Abstract

We propose a novel formulation to express the attachment of a polygonal surface to a skeleton using purely linear terms. This enables to simultaneously adapt the pose and shape of an articulated model in an efficient way. Our work is motivated by the difficulty to constrain a mesh when adapting it to multi-view silhouette images. However, such an adaption is essential when capturing the detailed temporal evolution of skin and clothing of a human actor without markers. While related work is only able to ensure surface consistency during mesh adaption, our coupled optimization of the skeleton creates structural stability and minimizes the sensibility to occlusions and outliers in input images. We demonstrate the benefits of our approach in an extensive evaluation. The skeleton attachment considerably reduces implausible deformations, especially when the number of input views is limited.