Dynamical and-or graph learning for object shape modeling and detection

Advances in Neural Information Processing Systems

Volumn 1, Issue , 2012, Pages 242-250

  Wang, Xiaolong ^a   Lin, Liang ^a  

^a SUN YAT SEN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKGROUND CLUTTER; DISCRIMINATIVE LEARNING; GRAPH MODEL; GRAPH REPRESENTATION; LOCAL PARTS; OBJECT SHAPE; OBJECT SHAPE MODELING; PART-BASED MODELS;

LEARNING ALGORITHMS;

ITERATIVE METHODS;

EID: 84877770379     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (27)

1. Y. Altun, I. Tsochantaridis, and T. Hofmann, Hidden markov support vector machines, In ICML, 2003.
2. M. Andriluka, S. Roth, and B. Schiele, Pictorial structures revisited: People detection and articulated pose estimation, In CVPR, 2009.
3. S. Belongie, J. Malik, and J. Puzicha, Shape Matching and Object Recognition using Shape Contexts, IEEE TPAMI, 24(1): 705-522, 2002.
4. L. Bourdev, S. Maji, T. Brox, and J. Malik, Detecting people using mutually consistent poselet activations, In ECCV, 2010.
5. P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan, Object Detection with Discriminatively Trained Part-based Models, IEEE TPAMI, 2010.
6. V. Ferrari, F. Jurie, and C. Schmid, From Images to Shape Models for Object Detection, Int'l J. of Computer Vision, 2009.
7. V. Ferrari, L. Fevrier, F. Jerie, and C. Schmid, Groups of Adjacent Contour Segments for Object Detection, IEEE TPAMI, 30(1): 36-51, 2008.
8. N. Kambhatla and T. K. Leen, Dimension Reduction by Local Principal Component Analysis, Neural Computation, 9: 1493-1516, 1997.
9. C. Lu, L. J. Latecki, N. Adluru, X. Yang, and H. Ling, Shape Guided Contour Grouping with Particle Filters, In ICCV, 2009.
10. T. Ma and L. J. Latecki, From Partial Shape Matching through Local Deformation to Robust Global Shape Similarity for Object Detection, In CVPR, 2011.
11. S. Maji and J. Malik, Object Detection using a Max-Margin Hough Transform, In CVPR, 2009.
12. D. R. Martin, C. C. Fowlkes, and J. Malik, Learning to detect natural image boundaries using local brightness, color, and texture cues, IEEET PAMI, 26(5): 530-549, 2004.
13. J. C. Platt, Using analytic qp and sparseness to speed training of support vector machines, In Advances in Neural Information Processing Systems, pages 557-563, 1998.
14. P. Schnitzspan, M. Fritz, S. Roth, and B. Schiele, Discriminative structure learning of hierarchical representations for object detection, In CVPR, 2009.
15. Z. Song, Q. Chen, Z. Huang, Y. Hua, and S. Yan, Contextualizing Object Detection and Classification, In CVPR, 2010.
16. P. Srinivasan, Q. Zhu, and J. Shi, Many-to-one Contour Matching for Describing and Discrim-inating Object Shape, In CVPR, 2010.
17. D. Tran and D. Forsyth, Improved human parsing with a full relational model, In ECCV, 2010.
18. Y. Wang, D. Tran, and Z. Liao, Learning Hierarchical Poselets for Human Parsing, In CVPR, 2011.
19. X. Yang and L. J. Latecki, Weakly Supervised Shape Based Object Detection with Particle Filter, In ECCV, 2010.
20. B. Yao, A. Khosla, and L. Fei-Fei, Classifying Actions and Measuring Action Similarity by Modeling the Mutual Context of Objects and Human Poses, In ICML, 2011.
21. P. Yarlagadda, A. Monroy and B. Ommer, Voting by Grouping Dependent Parts, In ECCV, 2010.
22. C.-N. J. Yu and T. Joachims, Learning structural svms with latent variables, In ICML, 2009.
23. A. Yuille and A. Rangarajan, The concave-convex procedure(cccp), In NIPS, pages 1033-1040, 2001.
24. Y.B. Zhao and S.C. Zhu, Image Parsing via Stochastic Scene Grammar, In NIPS, 2011.
25. L. Zhu, Y. Chen, A. Yuille, and W. Freeman, Latent Hierarchical Structural Learning for Object Detection, In CVPR, 2010.
26. L. Zhu, Y. Chen, Y. Lu, C. Lin, and A. Yuille, Max Margin AND/OR Graph Learning for Parsing the Human Body, In CVPR, 2008.
27. S.C. Zhu and D. Mumford, A stochastic grammar of images, Foundations and Trends in Computer Graphics and Vision, 2(4): 259-362, 2006.