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Abstract: This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information e#ciently. The learned model is used for automatic visual recognition and semantic segmentation of photographs. Our discriminative model exploits novel features, based on textons, which jointly model shape and texture. Unary classification and feature selection is achieved using shared boosting to give an e#cient classifier which can be applied... (Update)
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BibTeX entry: (Update)
@misc{ for-textonboost,
author = "Context Modeling For",
title = "TextonBoost: Joint Appearance, Shape and",
url = "citeseer.ist.psu.edu/761202.html" }
Citations (may not include all citations):236 Additive logistic regression: a statistical view of boosting - Friedman, Hastie et al. - 1998
145 Rapid object detection using a boosted cascade of simple fea.. - Viola, Jones - 2001
76 Shape matching and object recognition using shape contexts - Belongie, Malik et al. - 2002
50 Object class recognition by unsupervised scale-invariant lea.. - Fergus, Perona et al. - 2003
48 Object recognition as machine translation: Learning a lexico.. - Duygulu, Barnard et al. - 2002
23 Representing and recognizing the visual appearance of materi.. (context) - Leung, Malik - 2001
21 Conditional random fields: Probabilistic models for segmenti.. (context) - erty, McCallum et al. - 2001
16 Interactive graph cuts for optimal boundary and region segme.. (context) - Boykov, Jolly - 2001
13 Statistical cues for domain specific image segmentation with.. (context) - Konishi, Yuille - 2000
7 Multiscale conditional random fields for image labeling - He, Zemel et al. - 2004
7 Discriminative fields for modeling spatial dependencies in n.. - Kumar, Herbert - 2004
5 Interleaved object categorization and segmentation - Leibe, Schiele - 2003
5 Interactive foreground extraction using iterated graph cuts (context) - Rother, Kolmogorov et al. - 2004
3 Image parsing: Unifying segmentation (context) - Tu, Chen et al. - 2003
2 Shape matching and object recognition using low distortion c.. (context) - Berg, Berg et al. - 2005
2 LOCUS: Learning Object Classes with Unsupervised Segmentatio.. (context) - Winn, Jojic - 2005
2 Piecewise training of undirected models (context) - Sutton, McCallum - 2005
2 A hierarchical field framework for unified context-based cla.. (context) - Kumar, Hebert - 2005
1 Categorization by learned universal visual dictionary (context) - Winn, Criminisi et al. - 2005
1 Boosting sex identification performance (context) - Baluja, Rowley - 2005
1 cient boosting procedures for multiclass object detection (context) - Torralba, Murphy et al. - 2004
1 A statistical approach to texture classification from single.. (context) - Varma, Zisserman - 2005
1 of IEEE CVPR (context) - Kumar, Torr et al. - 2005
1 Combining top-down and bottom-up segmentation (context) - Borenstein, Sharon et al. - 2004
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