Active Pictorial Structures

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

Volumn 07-12-June-2015, Issue , 2015, Pages 5435-5444

  Antonakos, Epameinondas ^a   Alabort I Medina, Joan ^a   Zafeiriou, Stefanos ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DEFORMATION; GRAPHIC METHODS; INVERSE PROBLEMS; MARKOV PROCESSES; NORMAL DISTRIBUTION; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; TREES (MATHEMATICS);

ACTIVE APPEARANCE MODELS; DEFORMABLE MODELING; GAUSS-NEWTON OPTIMIZATION; GAUSSIAN MARKOV RANDOM FIELD; MULTIVARIATE DISTRIBUTIONS; PICTORIAL STRUCTURES; REAL TIME PERFORMANCE; STATE-OF-THE-ART METHODS;

COMPUTER VISION;

EID: 84959201593     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7299182     Document Type: Conference Paper

References (34)

1. J. Alabort-i Medina, E. Antonakos, J. Booth, P. Snape, and S. Zafeiriou. Menpo: A comprehensive platform for parametric image alignment and visual deformable models. In Proceedings of the ACM International Conference on Multimedia, MM '14, pages 679-682, New York, NY, USA, 2014. ACM.
2. J. Alabort-i-Medina and S. Zafeiriou. Bayesian active appearance models. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3438-3445,2014.
3. M. Andriluka, S. Roth, and B. Schiele. Pictorial structures revisited: People detection and articulated pose estimation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1014-1021,2009.
4. E. Antonakos, J. Alabort-i-Medina, G. Tzimiropoulos, and S. Zafeiriou. Hog active appearance models. In Proceedings of IEEE Conference on Image Processing (IClP), pages 224-228,2014.
5. S. Baker and I. Matthews. Lucas-kanade 20 years on: A unifying framework. International Journal of Computer Vision (llCV), 56(3):221-255, 2004.
6. P. N. Belhumeur, D. W. Jacobs, D. Kriegman, and N. Kumar. Localizing parts of faces using a consensus of exemplars. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 545-552, 20 II.
7. T. F. Cootes, G. J. Edwards, and C. J. Taylor. Active appearance models. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 23(6):681-685, 2001.
8. 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.
9. D. Cristinacce and T. Cootes. Automatic feature localisation with constrained local models. Pattern Recognition, 41(10):3054-3067,2008.
10. P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained partbased models. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 32(9):1627-1645, 2010.
11. P. F. Felzenszwalb and D. P. Huttenlocher. Efficient matching of pictorial structures. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 66-73,2000.
12. P. F. Felzenszwalb and D. P. Huttenlocher. Pictorial structures for object recognition. International Journal of Computer Vision (llCV), 61(1):55-79, 2005.
13. M. A. Fischler and R. A. Elschlager. The representation and matching of pictorial structures. IEEE Transactions on Computers, 22(1):67-92, 1973.
14. R. Gross, I. Matthews, and S. Baker. Generic vs. person specific active appearance models. Image and Vision Computing, 23(12):1080-1093, 2005.
15. G. D. Hager and P. N. Belhumeur. Efficient region tracking with parametric models of geometry and illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 20(10):1025-1039,1998.
16. V. Kazemi and J. Sullivan. One millisecond face alignment with an ensemble of regression trees. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1867-1874,2014.
17. D. G. Lowe. Object recognition from local scale-invariant features. In Proceedings of IEEE International Conference on Computer Vision (ICCV), volume 2, pages 1150-1157, 1999.
18. M. Mathias, R. Benenson, M. Pedersoli, and L. Van Gool. Face detection without bells and whistles. In European Conference on Computer Vision (ECCV), pages 720-735. Springer, 2014.
19. I. Matthews and S. Baker. Active appearance models revisited. International Journal of Computer Vision (llCV), 60(2):135-164,2004.
20. G. Papandreou and P. Maragos. Adaptive and constrained algorithms for inverse compositional active appearance model fitting. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1-8,2008.
21. S. Ren, X. Cao, Y. Wei, and 1. Sun. Face alignment at 3000 fps via regressing local binary features. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1685-1692,2014.
22. H. Rue and L. Held. Gaussian Markov random fields: theory and applications. CRC Press, 2005.
23. c. Sagonas, G. Tzimiropoulos, S. Zafeiriou, and M. Pantic. 300 faces in-the-wild challenge: The first facial landmark localization challenge. In Proceedings of IEEE International Conference on Computer Vision Workshopw (ICCV'W), pages 397-403, 2013.
24. C. Sagonas, G. Tzimiropoulos, S. Zafeiriou, and M. Pantic. A semi-automatic methodology for facial landmark annotation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 896-903, 2013.
25. J. M. Saragih, S. Lucey, and J. F. Cohn. Deformable model fitting by regularized landmark mean-shift. International Journal of Computer Vision (llCV), 91(2):200-215, 2011.
26. J. R. Tena, F. De la Torre, and I. Matthews. Interactive region-based linear 3d face models. ACM Transactions on Graphics (TOG), 30(4):76, 2011.
27. G. Tzimiropoulos, J. Alabort-i-Medina, S. Zafeiriou, and M. Pantic. Generic active appearance models revisited. In Asian Conference on Computer Vision (ACCV), pages 650-663. Springer, 2013.
28. G. Tzimiropoulos and M. Pantic. Optimization problems for fast aam fitting in-the-wild. In Proceedings of IEEE International Conference on Computer Vision (ICCV), pages 593-600,2013.
29. G. Tzimiropoulos and M. Pantic. Gauss-Newton deformable part models for face alignment in-the-wild. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1851-1858,2014.
30. Y. Wang, S. Lucey, and 1. F. Cohn. Enforcing convexity for improved alignment with constrained local models. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1-8,2008.
31. X. Xiong and F. De la Torre. Supervised descent method and its applications to face alignment. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 532-539, 2013.
32. Y. Yang and D. Ramanan. Articulated human detection with flexible mixtures of parts. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 35(12):2878-2890,2013.
33. X. Zhu and D. Ramanan. Face detection, pose estimation, and landmark localization in the wild. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2879-2886, 2012.
34. S. Zuffi, O. Freifeld, and M. 1. Black. From pictorial structures to deformable structures. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3546-3553, 2012.