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...
This work presents a real-time active vision tracking system based on log-polar image motion estimation with 2D geometric deformation models. We present a very efficient parametri...
Abstract. This paper presents a motion capture system using two cameras that is capable of estimating a constrained set of human postures in real time. We first obtain a 3D shape ...
Non-rigid structure from motion (NRSFM) is a difficult, underconstrained problem in computer vision. The standard approach in NRSFM constrains 3D shape deformation using a linear...
Abstract. This paper introduces a new model-based approach for simultaneously reconstructing 3D human motion and full-body skeletal size from a small set of 2D image features track...