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 paper describes methods for recovering time-varying shape and motion of nonrigid 3D objects from uncalibrated 2D point tracks. For example, given a video recording of a talkin...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
Thin plate spline (TPS) transformations have been applied to non-rigid shape matching with impressive results. However, existing methods often use a sparse set of point correspond...
Abstract. In this work, we present a method for the integration of feature and intensity information for non rigid registration. Our method is based on a free-form deformation mode...
Xenophon Papademetris, Andrea P. Jackowski, Robert...
We present a robust approach to creating 2.5D building models from aerial LiDAR point clouds. The method is guaranteed to produce crack-free models composed of complex roofs and ve...