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CVPR
2007
IEEE
14 years 9 months ago
Learning Conditional Random Fields for Stereo
State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose heuristic restrictions or priors on disparities, for e...
Daniel Scharstein, Chris Pal
ICPR
2008
IEEE
14 years 2 months ago
Combining shape-from-shading and stereo using Gaussian-Markov random fields
In this paper we present a method of combining stereo and shape-from-shading information, taking account of the local reliability of each shape estimate. Local estimates of dispar...
Tom S. F. Haines, Richard C. Wilson
CVPR
2009
IEEE
14 years 6 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
CVPR
2005
IEEE
14 years 9 months ago
A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
Qiang Ji, Yang Wang 0002
CVPR
2010
IEEE
14 years 1 months ago
Towards Semantic Embedding in Visual Vocabulary
Visual vocabulary serves as a fundamental component in many computer vision tasks, such as object recognition, visual search, and scene modeling. While state-of-the-art approaches...
R.-R. Ji, Hongxun Yao, Xiaoshuai Sun