We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
− We propose a vision based 3D object recognition and tracking system, which provides high level scene descriptions such as object identification and 3D pose information. The sys...
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
In this paper, we propose a physics-based and physiology-based approach for modeling real-time deformations of 3-D high-resolution polygonal lung models obtained from highresolutio...
Anand P. Santhanam, Celina Imielinska, Paul Davenp...
This paper presents a first set of experiments to integrate a realistic electro-mechanical model of a beating heart into simulated real-time three-dimensional (RT3D) ultrasound da...
Qi Duan, Philippe Moireau, Elsa D. Angelini, Domin...