Deep reconstruction models for image set classification

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 37, Issue 4, 2015, Pages 713-727

  Hayat, Munawar ^a   Bennamoun, Mohammed ^a   An, Senjian ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

auto encoders; deep learning; Image set classification; object recognition; video based face recognition

Indexed keywords

CAMERAS; FACE RECOGNITION; OBJECT RECOGNITION; SECURITY SYSTEMS;

AUTO ENCODERS; DEEP LEARNING; GAUSSIAN RESTRICTED BOLTZMANN MACHINES; GEOMETRIC STRUCTURE; IMAGE SETS; RECONSTRUCTION ERROR; STATE-OF-THE-ART METHODS; VIDEO-BASED FACE RECOGNITION;

IMAGE CLASSIFICATION;

EID: 84924588005     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2014.2353635     Document Type: Article

References (45)

1. W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld, "Face recognition: A literature survey, " ACM Comput. Surv., vol. 35, pp. 399-458, Dec. 2003.
2. A. Mian, M. Bennamoun, and R. Owens, "An efficient multimodal 2D-3D hybrid approach to automatic face recognition, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 11, pp. 1927-1943, Nov. 2007.
3. A. S. Mian, M. Bennamoun, and R. Owens, "Three-dimensional model-based object recognition and segmentation in cluttered scenes, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 10, pp. 1584-1601, Oct. 2006.
4. T.-K. Kim, J. Kittler, and R. Cipolla, "Discriminative learning and recognition of image set classes using canonical correlations, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 6, pp. 1005-1018, Jun. 2007.
5. R. Wang, S. Shan, X. Chen, and W. Gao, "Manifold-manifold distance with application to face recognition based on image set, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2008, pp. 1-8.
6. R. Wang and X. Chen, "Manifold discriminant analysis, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2009, pp. 429-436.
7. H. Cevikalp and B. Triggs, "Face recognition based on image sets, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2010, pp. 2567-2573.
8. M. T. Harandi, C. Sanderson, S. Shirazi, and B. C. Lovell, "Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2010, pp. 2705-2712.
9. Y. Hu, A. S. Mian, and R. Owens, "Face recognition using sparse approximated nearest points between image sets, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 10, pp. 1992-2004, Oct. 2012.
10. R. Wang, H. Guo, L. Davis, and Q. Dai, "Covariance discriminative learning: A natural and efficient approach to image set classification, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2012, pp. 2496-2503.
11. M. Yang, P. Zhu, L. V. Gool, and L. Zhang, "Face recognition based on regularized nearest points between image sets, " in Proc. 10th IEEE Int. Conf. Workshops Automat. Face Gesture Recognit., 2013, pp. 1-7.
12. E. Ortiz, A. Wright, and M. Shah, "Face recognition in movie trailers via mean sequence sparse representation-based classification, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2013, pp. 3531-3538.
13. P. Zhu, L. Zhang, W. Zuo, and D. Zhang, "From point to set: Extend the learning of distance metrics, " in Proc. Int. Conf. Comput. Vis., 2013, pp. 2664-2671.
14. M. Hayat, M. Bennamoun, and S. An, "Learning non-linear reconstruction models for image set classification, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2014, pp. 1915-1922.
15. O. Yamaguchi, K. Fukui, and K.-I. Maeda, "Face recognition using temporal image sequence, " in Proc. 3rd IEEE Int. Conf. Autom. Face Gesture Recognit., 1998, pp. 318-323.
16. M. Nishiyama, M. Yuasa, T. Shibata, T. Wakasugi, T. Kawahara, and O. Yamaguchi, "Recognizing faces of moving people by hierarchical image-set matching, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2007, pp. 1-8.
17. K.-C. Lee, J. Ho, M.-H. Yang, and D. Kriegman, "Video-based face recognition using probabilistic appearance manifolds, " in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., 2003, vol. 1, pp. 313-320.
18. R. Gross and J. Shi, "The CMU motion of body (mobo) database, " The Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA, Tech. Rep. CMU-RI-TR-01-18, 2001.
19. M. Kim, S. Kumar, V. Pavlovic, and H. Rowley, "Face tracking and recognition with visual constraints in real-world videos, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2008, pp. 1-8.
20. B. Y. Li, A. S. Mian, W. Liu, and A. Krishna, "Using Kinect for face recognition under varying poses, expressions, illumination and disguise, " in Proc. IEEE Workshop Appl. Comput. Vis., 2013, pp. 186-192.
21. G. Fanelli, J. Gall, and L. Van Gool, "Real time head pose estimation with random regression forests, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2011, pp. 617-624.
22. N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar, "Attribute and simile classifiers for face verification, " in Proc. IEEE Int. Conf. Comput. Vis., Oct. 2009, pp. 365-372.
23. L. Wolf, T. Hassner, and I. Maoz, "Face recognition in unconstrained videos with matched background similarity, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2011, pp. 529-534.
24. Z. Huang, S. Shan, H. Zhang, S. Lao, A. Kuerban, and X. Chen, "Benchmarking still-to-video face recognition via partial and local linear discriminant analysis on COX-S2V dataset, " in Proc. 11th Asian Conf. Comput. Vis., 2013, pp. 589-600.
25. B. Leibe and B. Schiele, "Analyzing appearance and contour based methods for object categorization, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2003, pp. 409-415.
26. Y. Bengio, A. Courville, and P. Vincent, "Representation learning: A review and new perspectives, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 8, pp. 1798-1828, Aug. 2013.
27. O. Arandjelovic, G. Shakhnarovich, J. Fisher, R. Cipolla, and T. Darrell, "Face recognition with image sets using manifold density divergence, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2005, vol. 1, pp. 581-588.
28. P. Turaga, A. Veeraraghavan, A. Srivastava, and R. Chellappa, "Statistical computations on Grassmann and Stiefel manifolds for image and video-based recognition, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 11, pp. 2273-2286, Nov. 2011.
29. J. Hamm and D. D. Lee, "Grassmann discriminant analysis: A unifying view on subspace-based learning, " in Proc. 25th Int. Conf. Mach. Learn., 2008, pp. 376-383.
30. M. T. Harandi, C. Sanderson, A. Wiliem, and B. C. Lovell, "Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures, " in Proc. IEEE Workshop Appl. Comput. Vis., 2012, pp. 433-439.
31. G. E. Hinton, S. Osindero, and Y.-W. Teh, "A fast learning algorithm for deep belief nets, " Neural Comput., vol. 18, no. 7, pp. 1527-1554, 2006.
32. P. Smolensky, "Information processing in dynamical systems: Foundations of harmony theory, " in Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1. Cambridge, MA, USA: MIT Press, 1986.
33. H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng, "Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, " in Proc. 26th Annu. Int. Conf. Mach. Learn., 2009, pp. 609-616.
34. G. W. Taylor, R. Fergus, Y. LeCun, and C. Bregler, "Convolutional learning of spatio-temporal features, " in Proc. Eur. Conf. Comput. Vis., 2010, pp. 140-153.
35. G. E. Hinton and R. R. Salakhutdinov, "Reducing the dimensionality of data with neural networks, " Science, vol. 313, no. 5786, pp. 504-507, 2006.
36. G. Hinton, S. Osindero, M. Welling, and Y.-W. Teh, "Unsupervised discovery of nonlinear structure using contrastive backpropagation, " Cognit. Sci., vol. 30, no. 4, pp. 725-731, 2006.
37. M. A. Carreira-Perpinan and G. E. Hinton, "On contrastive divergence learning, " in Proc. Artif. Intell. Stat., 2005, p. 17.
38. N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, "Smote: Synthetic minority over-sampling technique, " J. Artif. Intell. Res., vol. 16, no. 1, pp. 321-357, 2002.
39. T. Ojala, M. Pietikainen, and T. Maenpaa, "Multiresolution grayscale and rotation invariant texture classification with local binary patterns, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 7, pp. 971-987, Jul. 2002.
40. I. Naseem, R. Togneri, and M. Bennamoun, "Linear regression for face recognition, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 11, pp. 2106-2112, Nov. 2010.
41. P. Viola and M. J. Jones, "Robust real-time face detection, " Int. J. Comput. Vis., vol. 57, no. 2, pp. 137-154, 2004.
42. D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang, "Incremental learning for robust visual tracking, " Int. J. Comput. Vis., vol. 77, nos. 1/3, pp. 125-141, 2008.
43. G. Hinton, "A practical guide to training restricted Boltzmann machines, " Momentum, vol. 9, no. 1, p. 926, 2010.
44. Y. Bengio, "Practical recommendations for gradient-based training of deep architectures, " in Proc. Neural Netw.: Tricks Trade, 2012, pp. 437-478.
45. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma, "Robust face recognition via sparse representation, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 210-227, Feb. 2009.