Abstract. Foreground and background segmentation is a typical problem in computer vision and medical imaging. In this paper, we propose a new learning based approach for 3D segment...
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...
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
This paper addresses signal processing issues related to coded representation, reconstruction and rendering of multiview video for 3D displays. We provide an overview of standardi...
Anthony Vetro, Sehoon Yea, Matthias Zwicker, Wojci...
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...