Facial feature tracking under varying facial expressions and face poses based on restricted boltzmann machines

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2013, Pages 3452-3459

  Wu, Yue ^a   Wang, Zuoguan ^a   Ji, Qiang ^a  

^a RENSSELAER POLYTECHNIC INSTITUTE   (United States)

Author keywords

Facial feature tracking; Restricted Boltzmann Machines

Indexed keywords

BENCHMARK DATABASE; DEEP BELIEF NETWORKS; FACIAL EXPRESSIONS; FACIAL FEATURE POINTS; FACIAL FEATURE TRACKING; IMAGE MEASUREMENTS; NON-TRIVIAL TASKS; RESTRICTED BOLTZMANN MACHINE;

COMPUTER SCIENCE; ELECTRICAL ENGINEERING; PATTERN RECOGNITION; SOFTWARE ENGINEERING;

FACE RECOGNITION;

EID: 84887383616     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.443     Document Type: Conference Paper

References (24)

1. P. Belhumeur, D. Jacobs, D. Kriegman, and N. Kumar. Localizing parts of faces using a consensus of exemplars. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2729-2736, 2011. 2
2. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham. Active shape models their training and application. Computer Vision and Image Understanding, 61(1):38-59, 1995. 2
3. M. Dantone, J. Gall, G. Fanelli, and L. Van Gool. Real-time facial feature detection using conditional regression forests. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2578-2585, 2012. 2
4. L. Ding and A. Martinez. Features versus context: An approach for precise and detailed detection and delineation of faces and facial features. Pattern Analysis and Machine Intelligence, 32(11):2022-2038, 2010. 2
5. S. Eslami, N. Heess, and J. Winn. The shape boltzmann machine: a strong model of object shape. In CVPR, pages 406-413, 2012. 1, 2, 3, 7
6. G. Hinton. Training products of experts by minimizing contrastive divergence. Neural Computation, 14(8):1771-1800, August 2002. 3, 4
7. Y. Huang, Q. Liu, and D. Metaxas. A component-based framework for generalized face alignment. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41(1):287-298, 2011. 2
8. J. R. joshua M. Susskind, Geoffrey E. Hinton and A. K. Anderson. Generating facial expressions with deep belief nets. Affective Computing, Focus on Emotion Expression, Synthesis and Recognition, 2008. 2
9. Y. li Tian, T. Kanade, and J. F. Cohn. Recognizing action units for facial expression analysis. Pattern Analysis and Machine Intelligence, 23(2):97-115, February 2001. 2
10. P. Lucey, J. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews. The extended cohn kanade dataset: A complete dataset for action unit and emotion specified expression. In IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 94-101, 2010. 5
11. P. Luo. Hierarchical face parsing via deep learning. In CVPR, pages 2480-2487, 2012. 2
12. I. Matthews and S. Baker. Active appearance models revisited. Int. J. Comput. Vision, 60(2):135-164, 2004. 2, 5
13. R. Memisevic and G. E. Hinton. Learning to represent spatial transformations with factored higher-order boltzmann machines. Neural Comput., 22(6):1473-1492, 2010. 1, 4
14. A. Mohamed, G. Dahl, and G. Hinton. Acoustic modeling using deep belief networks. IEEE Transactions on Audio, Speech, and Language Processing, PP(99):1, 2011. 3
15. M. Pantic, M. F. Valstar, R. Rademaker, and L. Maat. Webbased database for facial expression analysis. In Proc. of IEEE Intl. Conf. on Multimedia and Expo, pages 317-321, 2005. 5, 6
16. P. Phillips, H. Moon, S. Rizvi, and P. Rauss. The feret evaluation methodology for face-recognition algorithms. Pattern Analysis and Machine Intelligence, 22(10):1090-1104, 2000. 6
17. G. Taylor, L. Sigal, D. Fleet, and G. Hinton. Dynamical binary latent variable models for 3d human pose tracking. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 631-638, 2010. 1, 2, 3
18. Y. Tong,W. Liao, and Q. Ji. Facial action unit recognition by exploiting their dynamic and semantic relationships. Pattern Analysis and Machine Intelligence, 29(10):1683-1699, oct. 2007. 5, 6
19. Y. Tong, Y. Wang, Z. Zhu, and Q. Ji. Robust facial feature tracking under varying face pose and facial expression. Pattern Recognition, 40(11):3195-3208, Nov. 2007. 2, 6, 7
20. M. Valstar, B. Martinez, X. Binefa, and M. Pantic. Facial point detection using boosted regression and graph models. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2729-2736, 2010. 2
21. M. Valstar, B. Martinez, X. Binefa, and M. Pantic. Facial point detection using boosted regression and graph models. In IEEE Conference on Computer Vision and Pattern Recognition, pages 2729-2736, june 2010. 6
22. Z. Wang, S. Lyu, G. Schalk, and Q. Ji. Learning with target prior. In Annual Conference on Neural Information Processing Systems (NIPS), 2012. 2
23. Z. Wang, S. Lyu, G. Schalk, and Q. Ji. Deep feature learning using target priors with applications in ecog signal decoding for bci. In International Joint Conferences on Artificial Intelligence (IJCAI), 2013. 2
24. R. B. Wilbur and A. C. Kak. Purdue rvl-slll american sign language database. Technical report, Purdue University, 2006. 5, 6