Non-rigid 3D shape recovery is an inherently ambiguous problem. Given a specific rigid motion, different non-rigid shapes can be found that fit the measurements. To solve this am...
We present a system that can segment articulated, non-rigid motion without a priori knowledge of the number of clusters present in the analyzed scenario. We combine existing algori...
We address the problem of non-rigid motion and correspondence estimation in 3D images in the absense of prior domain information. A generic framework is utilized in which a soluti...
This paper presents a method to efficiently estimate average 3-D shapes from non-rigid motion in the case of missing data. Such a shape can be further used to accomplish full reco...
— Most robotic vision algorithms are proposed by envisaging robots operating in structured environments where the world is assumed to be rigid. These algorithms fail to provide o...
* We present a novel approach for grouping from motion, based on a 4-D Tensor Voting computational framework. From sparse point tokens in two frames we recover the dense velocity f...
We present our system for the capturing and analysis of 3D facial motion. A high speed camera is used as capture unit in combination with two surface mirrors. The mirrors provide ...
Within this paper a new framework for Bayesian tracking is presented, which approximates the posterior distribution at multiple resolutions. We propose a tree-based representation...
Bjoern Stenger, Arasanathan Thayananthan, Philip H...