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ICIP
2010
IEEE
15 years 1 months ago
Fast semantic scene segmentation with conditional random field
In this paper, we present a fast approach to obtain semantic scene segmentation with high precision. We employ a two-stage classifier to label all image pixels. First, we use the ...
Wen Yang, Dengxin Dai, Bill Triggs, Gui-Song Xia, ...
CVPR
2004
IEEE
16 years 5 months ago
Efficient Belief Propagation for Early Vision
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher
154
Voted
ICCV
2007
IEEE
16 years 5 months ago
Applications of parametric maxflow in computer vision
The maximum flow algorithm for minimizing energy functions of binary variables has become a standard tool in computer vision. In many cases, unary costs of the energy depend linea...
Vladimir Kolmogorov, Yuri Boykov, Carsten Rother
173
Voted
MM
2006
ACM
221views Multimedia» more  MM 2006»
15 years 9 months ago
Video object segmentation by motion-based sequential feature clustering
Segmentation of video foreground objects from background has many important applications, such as human computer interaction, video compression, multimedia content editing and man...
Mei Han, Wei Xu, Yihong Gong
CVPR
2008
IEEE
16 years 5 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel