Dynamic bayesian network for unconstrained face recognition in surveillance camera networks

IEEE Journal on Emerging and Selected Topics in Circuits and Systems

Volumn 3, Issue 2, 2013, Pages 155-164

  An, Le ^a   Kafai, Mehran ^b   Bhanu, Bir ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b University of California Riverside   (United States)

Author keywords

Camera networks; dynamic Bayesian network (DBN); face recognition; surveillance

Indexed keywords

CAMERA NETWORK; DYNAMIC BAYESIAN NETWORKS; MULTI-CAMERA NETWORKS; PROBABILISTIC APPROACHES; RECOGNITION ACCURACY; RECOGNITION PERFORMANCE; SECURITY AND SURVEILLANCES; SURVEILLANCE CAMERAS;

CAMERAS; FACE RECOGNITION; MONITORING; SPACE SURVEILLANCE;

SECURITY SYSTEMS;

EID: 84879119744     PISSN: 21563357     EISSN: None     Source Type: Journal    
DOI: 10.1109/JETCAS.2013.2256752     Document Type: Article

References (37)

1. J. Han and B. Bhanu, "Individual recognition using gait energy image," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 2, pp. 316-322, Feb. 2006.
2. M. Grgic, K.Delac, and S. Grgic, "SCface-Surveillance cameras face database," Multimedia Tools Appl., vol. 51, no. 3, pp. 863-879, Feb. 2011.
3. Y. M. Lui, D. Bolme, B. Draper, J. Beveridge, G. Givens, and P. Phillips, "A meta-analysis of face recognition covariates," in Proc. IEEE 3rd Int. Conf. Biometrics: Theory, Appl., Syst., Sep. 2009, pp. 1-8.
4. Y. Wong, S. Chen, S. Mau, C. Sanderson, and B. Lovell, "Patchbased probabilistic image quality assessment for face selection and improved video-based face recognition," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Workshops, Jun. 2011, pp. 74-81.
5. 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. (CVPR), Jun. 2003, vol. 1, pp. 313-320.
6. W. Fan, Y. Wang, and T. Tan, , T. Kanade,A. Jain, andN.Ratha, Eds., "Video-based face recognition using Bayesian inference model," in Audio-and Video-Based Biometric Person Authentication, ser. Lecture Notes in Computer Science. Berlin, Germany: Springer, 2005, vol. 3546, pp. 122-130.
7. W. Liu, Z. Li, and X. Tang, "Spatio-temporal embedding for statistical face recognition from video," in Proc. Eur. Conf. Comput. Vis., 2006, pp. 374-388.
8. X. Liu and T. Cheng, "Video-based face recognition using adaptive hidden Markov models," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., Jun. 2003, vol. 1, pp. 340-345.
9. J. Stallkamp, H. Ekenel, and R. Stiefelhagen, "Video-based face recognition on real-world data," in Proc. IEEE 11th Int. Conf. Comput. Vis., Oct. 2007, pp. 1-8.
10. S. Biswas, G. Aggarwal, and P. Flynn, "Face recognition in low-resolution videos using learning-based likelihood measurement model," in Int. Joint Conf. Biometr., Oct. 2011, pp. 1-7.
11. B. Xie, V. Ramesh, Y. Zhu, and T. Boult, "On channel reliability measure training for multi-camera face recognition," in Proc. IEEE Workshop Appl. Comput. Vis., Feb. 2007, p. 41.
12. J. Harguess, C. Hu, and J. Aggarwal, "Fusing face recognition from multiple cameras," in Proc. IEEE Workshop Appl. Comput. Vis., Dec. 2009, pp. 1-7.
13. Z.Cui, S. Shan, H. Zhang, S. Lao, andX.Chen, "Image sets alignment for video-based face recognition," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2012, pp. 2626-2633.
14. Y. Xu, A. Roy-Chowdhury, and K. Patel, "Pose and illumination invariant face recognition in video," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit.Workshop Biometr., Jun. 2007, pp. 1-7.
15. U. Park, H. Chen, and A. Jain, "3D model-assisted face recognition in video," in Proc. 2nd Can. Conf. Comput. Robot Vis., May 2005, pp. 322-329.
16. C.-T. Liao, S.-F. Wang, Y.-J. Lu, and S.-H. Lai, "Video-based face recognition based on view synthesis from 3D face model reconstructed from a single image," in Proc. IEEE Int. Conf. Multimedia Expo, Apr. 2008, pp. 1589-1592.
17. M. Turk and A. Pentland, "Eigenfaces for recognition," J. Cogn. Neurosci. vol. 3, no. 1, pp. 71-86, Jan. 1991.
18. P. Viola and M. J. Jones, "Robust real-time face detection," Int. J. Comput. Vision vol. 57, no. 2, pp. 137-154, May 2004.
19. M. Bäuml, K. Bernardin, M. Fischer, H. Ekenel, and R. Stiefelhagen, "Multi-pose face recognition for person retrieval in camera networks," in Proc. 7th IEEE Int. Conf. Adv. Video Signal Based Surveill, Sep. 2010, pp. 441-447.
20. B. Lovell, S. Chen, A. Bigdeli, E. Berglund, and C. Sanderson, "On intelligent surveillance systems and face recognition for mass transport security," in Proc. Int. Conf. Control, Automat., Robot. Vis., Dec. 2008, pp. 713-718.
21. C. Shan, "Face recognition and retrieval in video," in Video Search and Mining, D. Schonfeld, C. Shan, D. Tao, and L. Wang, Eds. Berlin, Germany: Springer, 2010.
22. G. Heusch and S. Marcel, "Bayesian networks to combine intensity and color information in face recognition," in Proc. 3rd Int. Conf. Adv. Biometr., Berlin, Germany, 2009, pp. 414-423.
23. A. Nefian, "Embedded Bayesian networks for face recognition," in Proc. IEEE Int. Conf. Multimedia Expo., 2002, vol. 2, pp. 133-136.
24. A. V. Nefian, L. Liang, X. Pi, X. Liu, and K. Murphy, "Dynamic Bayesian networks for audio-visual speech recognition," EURASIP J. Appl. Signal Process. vol. 2002, no. 1, pp. 1274-1288, Jan. 2002.
25. M. Kafai and B. Bhanu, "Dynamic Bayesian networks for vehicle classification in video," IEEE Trans. Ind. Informat., vol. 8, no. 1, pp. 100-109, Feb. 2012.
26. T. Wang, Q. Diao, Y. Zhang, G. Song, C. Lai, and G. Bradski, "A dynamic Bayesian network approach to multi-cue based visual tracking," in Proc. Int. Conf. Pattern Recognit., Aug. 2004, vol. 2, pp. 167-170, vol. 2.
27. Y. Zhang and Q. Ji, "Active and dynamic information fusion for facial expression understanding fromimage sequences," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 5, pp. 699-714, May 2005.
28. D. Bouchaffra, "Topological dynamic Bayesian networks: Application to human face identification across ages," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. Workshops, Jun. 2010, pp. 1-8.
29. L. An, M. Kafai, and B. Bhanu, "Face recognition in multi-camera surveillance videos using dynamic Bayesian network," in Proc. 6th ACM/IEEE Int. Conf. Distrib. Smart Cameras, Oct. 2012, pp. 1-6.
30. T. Ahonen, A. Hadid, andM. Pietikäinen, "Face recognition with local binary patterns," in Eur. Conf. Comput. Vis., 2004, pp. 469-481.
31. T. Ahonen, E. Rahtu, V. Ojansivu, and J. Heikkila, "Recognition of blurred faces using local phase quantization," in Proc. 19th Int. Conf. Pattern Recognit., Dec. 2008, pp. 1-4.
32. G. Cooper and E. Herskovits, "A Bayesian method for the induction of probabilistic networks from data," Mach. Learn., vol. 9, no. 4, pp. 309-347, 1992.
33. T. Xiang and S. Gong, "Visual learning given sparse data of unknown complexity," in Proc. 10th IEEE Int. Conf. Comput. Vis., Oct. 2005, vol. 1, pp. 701-708.
34. N. Poh, C. H. Chan, J. Kittler, S.Marcel, C. McCool, E. Rúa, J. Castro, M. Villegas, R. Paredes, V. ? Struc, N. Pave?si?, A. Salah, H. Fang, and N. Costen, "An evaluation of video-to-video face verification," IEEE Trans. Inf. Forensics Security, vol. 5, no. 4, pp. 781-801, Dec. 2010.
35. W. Zhang, S. Shan, W. Gao, X. Chen, and H. Zhang, "Local Gabor binary pattern histogram sequence (LGBPHS): A novel non-statistical model for face representation and recognition," inProc. 10th IEEE Int. Conf. Comput. Vis., Oct. 2005, vol. 1, pp. 786-791.
36. O. Dèniz, G. Bueno, J. Salido, and F. D. la Torre, "Face recognition using histograms of oriented gradients," Pattern Recognit. Lett. vol. 32, no. 12, pp. 1598-1603, 2011.
37. S. B. Bengio, J. Marithoz, and M. Keller, "The expected performance curve," in Proc. 22nd Int. Conf. Mach. Learn., 2005, pp. 9-16.