메뉴 건너뛰기




Volumn , Issue , 2011, Pages 196-203

A hierarchical conditional random field model for labeling and classifying images of man-made scenes

Author keywords

[No Author keywords available]

Indexed keywords

CONDITIONAL RANDOM FIELD; DATA SETS; FUNDAMENTAL PROBLEM; GLOBAL LEVELS; HIERARCHICAL STRUCTURES; MULTISCALES; OBJECT CLASS; RANDOMIZED DECISIONS; SCENE INTERPRETATION;

EID: 84856682563     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130243     Document Type: Conference Paper
Times cited : (56)

References (36)
  • 6
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman. Random forests. Machine Learning, 45(1):5-32, 2001.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 14
    • 33745837462 scopus 로고    scopus 로고
    • Learning and incorporating top-down cues in image segmentation
    • X. He, R. Zemel, and D. Ray. Learning and incorporating top-down cues in image segmentation. In European Conference on Computer Vision, pages 338-351, 2006.
    • (2006) European Conference on Computer Vision , pp. 338-351
    • He, X.1    Zemel, R.2    Ray, D.3
  • 16
    • 61349174704 scopus 로고    scopus 로고
    • Robust higher order potentials for enforcing label consistency
    • P. Kohli, L. Ladicky, and P. Torr. Robust Higher Order Potentials for Enforcing Label Consistency. International Journal of Computer Vision, 82(3):302-324, 2009.
    • (2009) International Journal of Computer Vision , vol.82 , Issue.3 , pp. 302-324
    • Kohli, P.1    Ladicky, L.2    Torr, P.3
  • 19
    • 0344120654 scopus 로고    scopus 로고
    • Discriminative random fields: A discriminative framework for contextual interaction in classification
    • S. Kumar and M. Hebert. Discriminative random fields: A discriminative framework for contextual interaction in classification. In IEEE International Conference on Computer Vision, volume 2, pages 1150-1157, 2003.
    • (2003) IEEE International Conference on Computer Vision , vol.2 , pp. 1150-1157
    • Kumar, S.1    Hebert, M.2
  • 21
    • 0142192295 scopus 로고    scopus 로고
    • Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
    • J. Lafferty, A. McCallum, and F. Pereira. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In International Conference on Machine Learning, pages 282-289, 2001.
    • (2001) International Conference on Machine Learning , pp. 282-289
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 23
    • 33745827322 scopus 로고    scopus 로고
    • Learning to combine bottom-up and top-down segmentation
    • A. Levin and Y. Weiss. Learning to combine bottom-up and top-down segmentation. In European Conference on Computer Vision, pages 581-594, 2006.
    • (2006) European Conference on Computer Vision , pp. 581-594
    • Levin, A.1    Weiss, Y.2
  • 24
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • D. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91-110, 2004.
    • (2004) International Journal of Computer Vision , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.1
  • 26
    • 71149101357 scopus 로고    scopus 로고
    • Multi-class image segmentation using conditional random fields and global classification
    • N. Plath, M. Toussaint, and S. Nakajima. Multi-class image segmentation using conditional random fields and global classification. In International Conference on Machine Learning, pages 817-824, 2009.
    • (2009) International Conference on Machine Learning , pp. 817-824
    • Plath, N.1    Toussaint, M.2    Nakajima, S.3
  • 27
  • 29
    • 56749161398 scopus 로고    scopus 로고
    • Hierarchical support vector random fields: Joint training to combine local and global features
    • P. Schnitzspan, M. Fritz, and B. Schiele. Hierarchical support vector random fields: Joint training to combine local and global features. In European Conference on Computer Vision, pages 527-540, 2008.
    • (2008) European Conference on Computer Vision , pp. 527-540
    • Schnitzspan, P.1    Fritz, M.2    Schiele, B.3
  • 31
    • 33745824267 scopus 로고    scopus 로고
    • Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation
    • J. Shotton, JohnWinn, C. Rother, and A. Criminisi. Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation. In European Conference on Computer Vision, pages 1-15, 2006.
    • (2006) European Conference on Computer Vision , pp. 1-15
    • Shotton, J.1    Rother, J.C.2    Criminisi, A.3
  • 35
    • 80054037874 scopus 로고    scopus 로고
    • Regionwise classification of building facade images
    • Photogrammetric Image Analysis Springer
    • M. Y. Yang and W. F̈orstner. Regionwise Classification of Building Facade Images. In Photogrammetric Image Analysis, LNCS 6952, pages 209-220. Springer, 2011.
    • (2011) LNCS , vol.6952 , pp. 209-220
    • Yang, M.Y.1    F̈orstner, W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.