Object and action classification with latent variables

BMVC 2011 - Proceedings of the British Machine Vision Conference 2011

Volumn , Issue , 2011, Pages

  Bilen, Hakan ^a   Namboodiri, Vinay P ^a   Van Gool, Luc J ^a,b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS;

ACTION CLASSIFICATIONS; ACTION RECOGNITION; AUXILIARY INFORMATION; EXPERIMENTAL EVALUATION; GENERIC FRAMEWORKS; LATENT VARIABLE; MAX-MARGIN CLASSIFIERS; PARAMETER SPACES;

COMPUTER VISION;

EID: 84898440642     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C25.17     Document Type: Conference Paper

References (21)

1. Y. Bengio, J. Louradour, R. Collobert, and J. Weston. Curriculum learning. In Proc. Int. Conf. on Machine Learning (ICML), pages 41-48. ACM, 2009.
2. M. B. Blaschko, A. Vedaldi, and A. Zisserman. Simultaneous object detection and ranking with weak supervision. In Proc. of Advances in Neural Information Processing Systems (NIPS), 2010.
3. Y-Lan Boureau, Francis Bach, Yann LeCun, and Jean Ponce. Learning mid-level features for recognition. In Proc. of Computer Vision and Pattern Recognition (CVPR), pages 2559-2566, 2010.
4. M. Everingham, A. Zisserman, C. K. I. Williams, and L. Van Gool. The PASCAL Visual Object Classes Challenge 2006 (VOC2006) Results.
5. L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. In IEEE. CVPR 2004, Workshop on Generative-Model Based Vision, 2004.
6. Peter V. Gehler and Sebastian Nowozin. On feature combination for multiclass object classification. In Proc. of Int. Conf. on Computer Vision (ICCV), pages 221-228, 2009.
7. M. Pawan Kumar, Benjamin Packer, and Daphne Koller. Self-paced learning for latent variable models. In Proc. of Advances in Neural Information Processing Systems (NIPS), pages 1189-1197. 2010.
8. Ivan Laptev and Tony Lindeberg. Space-time interest points. In Proc. of Int. Conf. on Computer Vision (ICCV), pages 432-439, 2003.
9. Ivan Laptev, Marcin Marszałek, Cordelia Schmid, and Benjamin Rozenfeld. Learning realistic human actions from movies. In Proc. of Computer Vision and Pattern Recognition (CVPR), jun 2008.
10. Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In Proc. of Computer Vision and Pattern Recognition (CVPR), pages 2169-2178, 2006.
11. D.G. Lowe. Object recognition from local scale-invariant features. In Proc. of Int. Conf. on Computer Vision (ICCV), page 1150, 1999.
12. Ross Messing, Chris Pal, and Henry Kautz. Activity recognition using the velocity histories of tracked keypoints. In Proc. of Int. Conf. on Computer Vision (ICCV), Washington, DC, USA, 2009.
13. Axel Pinz. Object categorization. Foundations and Trends in Computer Graphics and Vision, 1(4), 2005.
14. Scott Satkin and Martial Hebert. Modeling the temporal extent of actions. In Proc. of European Conf. Computer Vision (ECCV), pages 536-548, 2010.
15. Christian Schüldt, Ivan Laptev, and Barbara Caputo. Recognizing human actions: A local svm approach. In Int. Conf. on Pattern Recognition (ICPR), pages 32-36, 2004.
16. I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun. Support vector machine learning for interdependent and structured output spaces. In Proc. Int. Conf. on Machine Learning (ICML), page 104, 2004.
17. A. Vedaldi and A. Zisserman. Structured output regression for detection with partial occulsion. In Proc. of Advances in Neural Information Processing Systems (NIPS), 2009.
18. Andrea Vedaldi, Varun Gulshan, Manik Varma, and Andrew Zisserman. Multiple kernels for object detection. In Proc. of Int. Conf. on Computer Vision (ICCV), pages 606-613, 2009.
19. Heng Wang, Muhammad Muneeb Ullah, Alexander Kläser, Ivan Laptev, and Cordelia Schmid. Evaluation of local spatio-temporal features for action recognition. In Proc. of British Machine Vision Conf. (BMVC), page 127, sep 2009.
20. Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas S. Huang, and Yihong Gong. Locality-constrained linear coding for image classification. In Proc. of Computer Vision and Pattern Recognition (CVPR), pages 3360-3367, 2010.
21. Chun-Nam John Yu and Thorsten Joachims. Learning structural svms with latent variables. In Proc. Int. Conf. on Machine Learning (ICML), pages 1169-1176, 2009.