This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
Abstract. In this paper we propose a probabilistic framework that models shape variations and infers dense and detailed 3D shapes from a single silhouette. We model two types of sh...
Traditionally, human facial expressions have been studied using either 2D static images or 2D video sequences. The 2D-based analysis is incapable of handing large pose variations....
Lijun Yin, Xiaozhou Wei, Yi Sun, Jun Wang, Matthew...
This paper presents a framework for construction of animated models from captured surface shape of real objects. Algorithms are introduced to transform the captured surface shape ...
In this paper we consider the problem of recovering the 3D motion and shape of an arbitrarily-moving, arbitrarilyshaped curve from multiple synchronized video streams acquired fro...