We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
New medical imaging modalities offering multi-valued data, such as phase contrast MRA and diffusion tensor MRI, require general representations for the development of automatized a...
Juan Ruiz-Alzola, Carl-Fredrik Westin, Simon K. Wa...
Semantic region labeling in outdoor scenes, e.g., identifying sky, grass, foliage, water, and snow, facilitates content-based image retrieval, organization, and enhancement. A maj...
Matthew R. Boutell, Jiebo Luo, Christopher M. Brow...
This paper generalizes Markov Random Field (MRF) stereo methods to the generation of surface relief (height) fields rather than disparity or depth maps. This generalization enable...
George Vogiatzis, Philip H. S. Torr, Steven M. Sei...
Despite recent advances in finding efficient LOD-representations for gigantic 3D objects, rendering of complex, gigabyte-sized models and environments is still a challenging tas...