Accurately identifying corresponded landmarks from a population of shape instances is the major challenge in constructing statistical shape models. In this paper, we address this ...
Pahal Dalal, Brent C. Munsell, Song Wang, Jijun Ta...
We describe an automatic method for building optimal 3D statistical shape models from sets of training shapes. Although shape models show considerable promise as a basis for segmen...
Rhodri H. Davies, Carole J. Twining, Timothy F. Co...
In this paper, we propose a novel 2D/3D approach for 3D model matching and retrieving. Each model is represented by a set of depth lines which will be afterward transformed into s...
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 an automatic annotation, or autotagging, algorithm that attaches textual tags to 3D models based on their shape and semantic classes. The proposed method emplo...