Recognition of humans and their activities using video

Synthesis Lectures on Image, Video, and Multimedia Processing

Volumn 1, Issue , 2005, Pages 1-173

  Chellappa, Rama ^a   Roy Chowdhury, Amit K ^b   Zhou, S Kevin ^c  

^a UNIVERSITY OF MARYLAND   (United States)

^b University of California Riverside   (United States)

^c SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

Face Recognition; Gait Recognition; Human Activity Recognition; Pattern Recognition

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; DIAGNOSIS; IMAGE RETRIEVAL; MATHEMATICAL MODELS; MULTIMEDIA SYSTEMS; RESEARCH AND DEVELOPMENT MANAGEMENT;

AUTOMATIC HUMAN IDENTIFICATION; GAIT RECOGNITION; HUMAN ACTIVITY RECOGNITION;

FACE RECOGNITION;

EID: 33845778451     PISSN: 15598136     EISSN: 15598144     Source Type: Book Series    
DOI: 10.2200/S00002ED1V01Y200508IVM001     Document Type: Article

References (199)

1. AFGR: Proceedings of 'IEEE International Conference on Automatic Face and Gesture Recognition, 1995, 1996, 1998, 2000, 2002.
2. AVBPA: Proceedings of International Conference on Audio, Video and Biometric Person Authentication, 1997, 1999, 2001, 2003.
3. J. J. Atick, P. A. Griffin, and A. N. Redlich, Statistical approach to shape from shading: Reconstruction of 3-dimensional face surfaces from single 2-dimensional images. NeurComp, 8(6):1321-1340, Aug. 1996.
4. D. Ayers and R. Chellappa, Scenario recognition from video using a hierarchy of dynamic belief networks. In Proc. of Intl. Conf. Pattern Recognition, 2000, pp. 835-838.
5. A. Azarbayejani, T. Starner, B. Horowitz, and A. P. Pentland, Visually controlled graphics. IEEE Trans. Pattern Anal. Machine Intell., 15:602-605, June 1993 doi:10.1109/34.216730
6. C. D. Barclay, J. E. Cutting, and L. T. Kozlowski, Temporal and spatial factors in gait perception that influence gender recognition. Perception Psychophy., 23:145-152, 1978.
7. P. Barral, G. Dorme, and D. Plemenos, Visual understanding of a scene by automatic movement of a camera. In. Int. Conf GraphiCon'99, 1999.
8. R. Basri and D. W. Jacobs, Lambertian reflectance and linear subspaces. IEEE Trans. Pattern Anal. Machine Intell., 25(2):218-233, Feb. 2003. doi:10.1109/TPAMI.2003.1177153
9. T. Beardsworth and T. Buckner, The ability to recognize oneself from a video recording of ones movements without seeing ones body. Bull. Psychonomic Soc., 18(1):19-22, 1981.
10. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, Eigenfaces vs. Fisher-faces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Machine Intell., 19:711-720, doi:10.1109/34.598228
11. I. Biederman and P. Kalocsai, Neural and psychophysical analysis of object and face recognition. In Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. F Soulie, and T. S. Huang, Eds. New York: Springer-Verlag, 1998, pp. 3-25.
12. A. Bissacco, A. Chiuso, Y. Ma, and S. Soatto, Recognition of human gaits. In Proc. of IEEE Computer Society Conf. Computer Vis. Pattern Recogn., Vol. 2, 2001, pp. 52-57.
13. M. J. Black and Y. Yacoob, Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion. In Proc. Int. Conf Comput. Vis., 1995, pp. 374-381.
14. D. Blackburn, M. Bone, and P. J. Phillips, Face recognition vendor test 2000. Technical report available at http://www.frvt.org, 2001.
15. V. Blanz and T. Vetter, Face recognition based on fitting a 3d morphable model. IEEE Trans. Pattern Anal. Machine Intell., 25(9):1063-1074, Sept. 2003. doi:10.1109/TPMI.2003.1227983
16. W. W. Bledsoe, The model method in facial recognition. Technical Report PRI:15, Panoramic Research, Inc., Palo Alto, CA, 1964.
17. A. F. Bobick and A. Johnson, Gait recognition using static activity-specific parameters. In Proc. IEEE Conf Comput. Vis. Pattern Recogn., Dec. 2001, pp. 423-430.
18. E. Borovikov and L. Davis, 3D shape estimation based on density driven model fitting. In Proc. 1st Int. Symp. 3D Data Process. Visual. Trans. (3DPVT), 2002.
19. M. Brand, Morphable 3D models from video. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2001, pp. 456-463.
20. M. Brand and R. Bhotika, Flexible flow for 3D nonrigid tracking and shape recovery. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2001, pp. 315-322.
21. C. Bregler, A. Hertzmann, and H. Biermann, Recovering non-rigid 3D shape from image streams. In Proc. IEEE Comput. Soc. Conf Comput. Vis. Pattern Recogn., 2000, pp. 690-696.
22. C. Bregler and J. Malik, Tracking people with twists and exponential maps. In Proc. IEEE Comput. Soc. Conf. Comput. Vu. Pattern Recogn., 1998, pp. 8-15.
23. B. F. Bremond and M. Thonnat, Analysis of human activities described by image sequences. In Proc. Intl. Florida AI Research Symp., 1997.
24. A. Burton-Jones, V.C. Storey, V. Sugumaran, and P. Ahluwalia, Assessing the effectiveness of the DAML ontologies for the semantic web. In Eighth Int. Conf. Appl. Natural Language to Inform. Syst., June 2003.
25. H. Buxton and S. Gong, Visual surveillance in a dynamic and uncertain world. Artif. Intell., 1995, Vol. 78: 431-459.
26. R. Cutler, C. Benabdelkader and L.S. Davis, Motion based recognition of people in eigengait space. In Proc. IEEE Conf. Face Gesture Recogn., 2002, pp. 267-272.
27. C. Castel, L. Chaudron, and C. Tessier, What is going on? A high-level interpretation of a sequence of images. In ECCV Workshop on Conceptual Descriptions from Images, 1996.
28. T. Choudhury, B. Clarkson, T. Jebara, and A. Pentland, Multimodal person recognition using unconstrained audio and video. In Proc. Intl. Conf. Audio, Video Biometric Person Authentication, 1999, pp. 176-181.
29. J. J. Clark and A. L. Yuille, Data Fusion for Sensory Information Processing Systems. Norwell, MA: Kluwer, 1990.
30. K. D. Cock and D. B. Moor, Subspace angles and distances between ARMA models. In Proc. Intl. Symp. Math. Theory Networks Syst., 2000.
31. R. Collins, R. Gross, and J. Shi, Silhouette-based human identification from body shape and gait. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., May 2002, pp. 351-356.
32. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham, Active shape models: Their training and application. Comput. Vis. Image Understand., 61:38-59, Jan. 1995. doi:10.1006/cviu.1995.1004
33. I. J. Cox, J. Ghosh, and P. N. Yianilos, Feature-based face recognition using mixture-distance. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1996, pp. 209-216.
34. D. Cunado, J. M. Nash, M. S. Nixon, and J. N. Carter, Gait extraction and description by evidence-gathering. In Proc. Int. Conf. Audio, Video Biometric Person Authentication, 1999, pp. 43-48.
35. J. Cutting and L. Kozlowski, Recognizing friends by their walk: Gait perception without familiarity cues. Bull. Psychonomic Soc., 9:353-356, 1977.
36. J. E. Cutting and D. R. Proffitt, Gait perception as an example of how we perceive events. In Intersensory Perception and Sensory Integration, R. D. Walk and H. L. Pick, Ed., London: Plenum Press, 1981.
37. J. Davis and A. Bobick, The representation and recognition of action using temporal templates. In Proc. IEEE Comput. Soci. Conf. Comput. Vis. Pattern Recogn., 1997, pp. 928-934.
38. A. Doucet, N. deFreitas, and N. Gordon, Sequential Monte Carlo Methods in Practice. New York: Springer, 2001.
39. C. Dousson, P. Gabarit, and M. Ghallab, Situation recognition: Representation and algorithms. In Proc. Int. Joint Conf. AI, 1993, pp. 166-172.
40. I. L. Dryden and K. V. Mardia, Statistical Shape Analysis. New York: John Wiley, 1998.
41. R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. New York: John Wiley, 2001.
42. G. J. Edwards, C. J. Taylor, and T. F. Cootes, Learning to identify and track faces in image sequences. In Proc. Int. Conf. Comput. Vis., 1998, pp. 317-322.
43. H. D. Ellis, Introduction to aspects of face processing: Ten questions in need of answers. In Aspects of Face Processing, H. Ellis, M. Jeeves, F. Newcombe, and A. Young, Eds. Dordrecht: Nijhoff, 1986, pp. 3-13.
44. K. Etemad and R. Chellappa, Discriminant analysis for recognition of human face images. J. Opt. Soc. Amer. A, 14:1724-1733, 1997.
45. O. D. Faugeras, Three-Dimensional Computer Vision: A Geometric Viewpoint. Cambridge, MA: MIT Press, 1993.
46. D. Forsyth, Shape from texture and integrability. In Proc. Int. Conf. Comput. Vis., 2001, pp. 447-453.
47. R. T. Frankot and R. Chellappa, A method for enforcing integrability in shape from shading problem. IEEE Trans. Pattern Anal. Machine Intell., 10(7):439-451, 1987.
48. W. T. Freeman and J. B. Tenenbaum, Learning bilinear models for two-factor problems in vision. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1997.
49. P. Fua, Regularized bundle-adjustment to model heads from image sequences without calibration data. Int. J. Comput. Vis., 38(2):153-171, July 2000. doi:10.1023/A:1008105802790
50. K. Fukunaga, Statistical Pattern Recognition. New York: Academic Press, 1989.
51. S. Furui, Cepstral analysis technique for automatic speaker verification. Proc. Intl. Conf. Acous., Speech Signal Process., 29(2):254-272, April 1981. doi:10.1109/TASSP.1981.1163530
52. I. Gauthier and N. K. Logothetis. Is face recognition so unique after all? J. Cognit. Neuropsychol., 17:125-142, 2000. doi:10.1080/026432900380535
53. D. M. Gavrila, The visual analysis of human movement: A survey. Comput. Vis. Image Understand., 73(1):82-98, Jan. 1999. doi:101006/cviu.1998.0716
54. S. Geman and D. Geman, Stochastic relaxation, gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intell., 6(6):721-741, Nov. 1984.
55. A. Georghiades, P. Belhumeur, and D. Kriegman, From few to many: Illumination cone models for face recognition under variable lighting and pose. IEEE Trans. PAMI, 23(6):643 -660, 2001.
56. G. Golub and C. V. Loan, Matrix Computations. Baltimore, MD: Johns Hopkins University Press, 1989.
57. S. Gong, S. McKenna, and A. Psarrou, Dynamic Vision: From Images to Face Recognition. Singapore: World Scientific, 2000.
58. W. E. L. Grimson, L. Lee, R. Romano, and C. StaufFer, Using adaptive tracking to classify and monitor activities in a site. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1998, pp. 22-31.
59. R. Gross and Jianbo Shi, The CMU motion of body (MOBO) database. Technical Report CMU-RI-TR-01-18, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, June 2001.
60. T. R. Gruber, Toward principles for the design of ontologies used for knowledge sharing. Int. J. Human-Comput. Stud., 1995.
61. G. Shakhnarovich, L. Lee, and T. Darrell, Integrated face and gait recognition from multiple views. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., Dec. 2001, pp. 439-446.
62. L. Gu, S. Z. Li, and H. J. Zhang, Learning probabilistic distribution model for multi-view face dectection. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2001.
63. I. Haritaoglu, D. Harwood, and L. S. Davis, Ghost: A human body part labeling system using silhouettes. In Proc. Int. Conf. Pattern Recogn., 1998, pp. 77-82.
64. G. F. Harris and P. A. Smith, Ed. Human Motion Analysis: Current Applications and Future Directions. Piscataway, NJ: IEEE Press, 1996.
65. R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision. Cambridge, UK: Cambridge University Press, 2000.
66. B. Heisele, T. Serre, M. Pontil, and T. Poggio, Component-based face detection. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2001, pp. 657-662.
67. L. Hong and A. Jain, Multimodal biometrics. In Biometrics: Personal Identification in a Networked Society, A. Jain, R. Bolle, and S. Pankanti, Ed., Norwell, MA: Kluwer, 1999.
68. S. Hongeng and R. Nevatia, Multi-agent event recognition. In Proc. Inf. Conf. Comput. Vis., 2001, pp. 84-91.
69. B. K. P. Horn and M. J. Brooks, Shape from Shading. Cambridge, MA: MIT Press, 1989.
70. P. S. Huang, C. J. Harris, and M. S. Nixon, Recognizing humans by gait via parametric canonical space. Artif. Intell. Eng., 13(4):359-366, Oct. 1999. doi:10.1016/S0954-1810(99)00008-4
71. T. Huang, D. Koller, J. Malik, G. Ogasawara, B. Rao, S. Russell, and J. Weber, Automatic symbolic traffic scene analysis using belief networks. In Proc. AAAI, 1994, pp. 966-972.
72. S. Intille and A. Bobick, A framework for recognizing multi-agent action from visual evidence. In Proc. AAAI, 1999, pp. 518-525.
73. Michael Isard and Andrew Blake, Contour tracking by stochastic propagation of conditional density. Proc. Eur. Conf. Comput. Vis., 1: 343-356, 1996.
74. T. Jebara, K. Russell, and A. Pentland, Mixtures of eigen features for real-time structure from texture. In Proc. Int. Conf. Comput. Vis., 1998, pp. 128-135.
75. T. S. Jebara and A. P. Pentland, Parameterized structure from motion for 3D adaptive feedback tracking of faces. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1997, pp. 144-150.
76. G. Johansson, Visual perception of biological motion and a model for its analysis. P and P, 14(2):201-211, 1973.
77. G. Johansson, Visual motion perception. Sci. Amer., 232:76-88, 1975.
78. I. Kakadiaris and D. Metaxas, Model-based estimation of 3D human motion. IEEE Trans. Pattern Anal. Machine Intell., 2000, 22(12):1453-1459. doi:10.1109/34.895978
79. A. Kale, A. Roy-Chowdhury, and R. Chellappa, Towards a view invariant gait recognition algorithm. In Proc. IEEE Conf. Advanced Video Signal Based Surveillance, 2003, pp. 143-150.
80. A. Kale, N. Cuntoor, B. Yegnanarayana, A. N. Rajagopalan, and R. Chellappa, Gait analysis for human identification. In Proc. Int. Conf. Audio, Video Biometric Person Authentication, 2003.
81. A. Kale, A. K. Roy-Chowdhury, and R. Chellappa, Gait-based human identification from a monocular video sequence. In Handbook on Pattern Recognition and Computer Vision, 3rd eds., C. H. Cheng and P. S. P. Wang, Ed. Singapore: World Scientific, to be Published.
82. T. Kanade, Computer Recognition of Human Faces. Basel: Birkhauser, 1973.
83. M. D. Kelly, Visual identification of people by computer. Technical Report AI-130, Stanford AI Project, Stanford, CA, 1970.
84. D. G. Kendall, D. Barden, T. K. Carne, and H. Le, Shape and Shape Theory. New York: John Wiley, 1999.
85. M. Kirby and L. Sirovich, Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Trans. Pattern Anal. Machine Intell., 12:103-108, Jan. 1990. doi:10.1109/34.41390
86. J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, On combining classifiers. IEEE Trans. Pattern Anal. Machine Intell., 20(3):226-239, March 1998. doi:10.1109/34.667881
87. B. Knight and A. Johnston, The role of movement in face recognition. Vis. Cogn., 4:265-274, 1997.
88. L. Kozlowski and J. Cutting, Recognizing the sex of a walker from a dynamic point display. Perception Psychophy., 21:575-580, 1977.
89. N. Kruger, M. Potzsch, and C. von der Malsburg, Determination of face position and pose with a learned representation based on labeled graphs. Image Vis. Comput., 15:665-673, Aug. 1997. doi:10.1016/S0262-8856(97)00012-7
90. Y. Kuniyoshi and H. Inoue, Qualitative recognition of ongoing human action sequences. In Proc. Int. Joint Conf. AI, 1993, pp. 1600-1609.
91. M. Lades, J. Vorbruggen, J. Buhmann, L. Lange, C. von der Malsburg, R. Wurtz, and W. Konen. Distortion invariant object recognition in the dynamic link architecture. IEEE Trans. Comput., 42:300-311, 1993. doi:10.1109/12.210173
92. A. Lanitis, C. J. Taylor, and T. F. Cootes, Automatic face identification system using flexible appearance models. Image Vis. Comput., 13:393-401, June 1995. doi:10.1016/0262-8856(95)99726-H
93. A. Laurentini, The visual hull concept for silhouette-based image understanding. IEEE Trans. Pattern Anal. Machine Intell., 16(2):150-162, Feb. 1994. doi:10.1109/34.273735
94. K. C. Lee, J. Ho, M. H. Yang, and D. J. Kriegman, Video-based face recognition using probabilistic appearance manifolds. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2003, pp. 313-320.
95. L. Lee and G. Dalley, Learning pedestrian models for silhouette refinement. In Proc. Int. Conf Comput. Vis., 2003, pp. 663-670.
96. L. Lee and W. E. L. Crimson, Gait analysis for recognition and classification. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 2002, pp.155-161.
97. M. Levoy and P. Hanrahan, Light field rendering. In Proc. ACM SIGGRAPH, New Orleans, LA, 1996.
98. B. Li and R. Chellappa, Face verification through tracking facial features. J. Opt. Soc. Amer. A, 18(12):2969-2981, Dec. 2001.
99. Y. M. Li, S. G. Gong, and H. Liddell, Constructing facial identity surfaces in a nonlinear discriminating space. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2001, pp. 258-263.
100. Y. M. Li, S. G. Gong, and H. Liddell, Modelling faces dynamically across views and over time. In Proc. Int. Conf. Comput. Vis., 2001, pp. 554-559.
101. S. H. Lin, S. Y. Kung, and L. J. Lin, Face recognition/detection by probabilistic decision-based neural network. IEEE Trans. Neural Networks, 8:114-132, 1997. doi:10.1109/72.554196
102. J. Little and J. Boyd, Recognizing people by their gait: The shape of motion. Videre, 1(2):1-32, 1998.
103. C. Liu and H. Wechsler, Evolutionary pursuit and its application to face recognition. IEEE Trans. Pattern Anal. Machine Intell., 22:570-582, June 2000. doi:10.1109/34.8631961
104. X. Liu and T. Chen, Video-based face recognition using adaptive hidden Markov models. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2003, pp. 340-345.
105. J. Matas et. al, Comparison of face verification results on the XM2VTS database. In Proc. Int. Conf Pattern Recogn., Vol. 4, 2000, pp. 858-863.
106. W. Matusik, C. Buehler, and L. McMillan, Polyhedral visual hulls for real-time rendering. In Proc. Eurographics Workshop Rendering'01, 2001.
107. W. Matusik, C. Buehler, R. Raskar, S. J. Gortler, and L. McMillan, Image-based visual hulls. In Proc. SIGGRAPH 2000, pp. 369-374.
108. T. Maurer and C. von der Malsburg, Single-view based recognition of faces rotated in depth. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 1996, pp 176-181.
109. S. McKenna and S. Gong, Recognising moving faces. In Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. F. Soulie, and T. S. Huang, Eds. Berlin: Springer-Verlag, 1998, pp. 578-588.
110. L. McMillan, An image-based approach to 3D computer graphics. Ph.D. Dissertation, University of North Carolina, 1997.
111. K. Messer, J. Matas, J. Kittler, J. Luettin, and G. Maitre, Xm2vtsdb: The extended M2VTS database. In Proc. Int. Conf. Audio, Video Biometric Person Authentication, 1999, pp. 72-77.
112. B. Moghaddam, T. Jebara, and Pentland A, Bayesian face recognition. Pattern Recogn., 33:1771-1780, 2000. doi:10.1016/S0031-3203(99)00179-X
113. B. Moghaddam and A. P. Pentland, Probabilistic visual learning for object representation. IEEE Trans. Pattern Anal. Machine Intell., 19:696-710, July 1997. doi:10.1109/34.598227
114. H. Moon, R. Chellappa, and A. Rosenfeld, Optimal edge based shape detection. IEEE Trans. Image Process., 11(11):1209-1227, Nov. 2002. doi:10.1109/TIP.2002.800896
115. M. P. Murray, A. B. Drought, and R. C. Kory, Walking patterns of normal men. J. Bone Joint Surg., 46-A(2):335-360, 1964.
116. E. Muybridge, The Human Figure in Motion. New York: Dover, 1901.
117. H. Nagel, From image sequences towards conceptual descriptions. Image Vis. Comput., 6:59-74, 1988. doi:10.1016/0262-8856(88)900001-7
118. V. Nalwa, A Guided Tour of Computer Vision. Reading, MA: Addison-Wesley, 1993.
119. B. Neumann and H.J. Novak, Event models for recognition and natural language descriptions of events in real-world image sequences. In Proc. Int. Joint Conf. AI, 1983, pp. 724-726.
120. R. Nevatia, J. Hobbs, and R. Bolles, An ontology for representing video events. In IEEE Workshop Event Mining-Detection Recogn. of Events in Video, 2004.
121. P.V. Overschee and B.D. Moor, Subspace algorithms for the stochastic identification problem. Automatica, 29:649-660, 1993. doi:10.1016/0005-1098(93) 90061-w
122. A. Papoulis, Probability, Random Variables and Stochastic Processes. New York: McGraw-Hill, 1991.
123. V. Parameswaran and R. Chellappa, Quasi-invariants for human action representation and recognition. In Proc. Int. Conf. Pattern Recogn., 2002, pp. 307-310.
124. V. Parmeswaran and R. Chellappa, View invariants for human action recognition. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2003, pp. 613-619.
125. J. Pearl, Probabilistic Reasoning in Intelligent Systems. San Mateo, CA: Morgan Kaufmann, 1988.
126. P. Penev and J. Atick, Local feature analysis: A general statistical theory for object representation. Network- Comput. Neural Syst., 7:477-500, 1996. doi:10.1088/0954-898X/7/3/002
127. A.P. Pentland, B. Moghaddam, and T. Starner, View-based and modular eigenspaces for face recognition. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1994.
128. P. J. Phillips, S. Sarkar, I. Robledo, P. Grother, and K. W. Bowyer, Baseline results for the challenge problem of human ID using gait analysis. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 2002, pp. 130-135.
129. P. J. Phillips, S. Sarkar, I. Robledo, P. Grother, and K. W. Bowyer, The gait identification challenge problem: Data sets and baseline algorithm. In Proc Int. Conf. Pattern Recogn., 2002, pp. 385-388.
130. P.J. Phillips, P.J. Grother, R.J. Micheals, D.M. Blackburn, E. Tabassi, and J.M. Bone, Face recognition vendor test 2002: Evaluation report. Technical Report NISTIR 6965, http://www.frvt.org, 2003.
131. P.J. Phillips, H. Moon, S. Rizvi, and P. Rauss, The FERET evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Machine Intell., 22:109-1104, Oct. 2000. doi:10.1109/34.879790
132. P.J. Phillips, H. Wechsler, J. Huang, and P.J. Rauss, The FERET database and evaluation procedure for face-recognition algorithms. Image Vis. Comput., 16:295-306, April 1998. doi:10.1016/S0262-8856(97)00070-X
133. M. Pollefeys, Self-calibration and metric 3D reconstruction from uncalibrated image sequences. Ph.D. Thesis, ESAT-PSI, K.U. Leuven, 1999.
134. L.R. Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE, 77(2):257-285, Feb. 1989. doi:10.1109/5.18626
135. C. Rao, A. Yilmaz, and M. Shah, View-invariant representation and recognition of actions. Int. J. Comput. Vis., 50(2):203-226, 2002. doi:10.1023/A:1020350100748
136. P. Remagnini, T. Tan, and K. Baker, Agent-oriented annotation in model based visual surveillance. In Proc. of International Conf. on Computer Vision, pages 857-862, 1998.
137. H. Robbins and S. Monro, A stochastic approximation method. Ann. Math. Stat., 22:400-407, 1951.
138. S. Romdhani, V. Blanz, and T. Vetter, Face identification by fitting a 3D morphable model using linear shape and texture error functions. In Proc. Eur. Conf. Comput. Vis., IV: 3ff, 2002.
139. N. Rota and M. Thonnat, Activity recognition from video sequence using declarative models. In Eur. Conf Artif. Intell., 2000.
140. H.A. Rowley, S. Baluja, and T. Kanade, Neural network based face detection. IEEE Trans. Patt. Anal. Machine Intell., 20:23-38, Jan. 1998. doi:10.1109/34.655647
141. A. K. Roy-Chowdhury, Statistical analysis of 3D modeling from monocular video streams. Ph.D. Thesis, Univeristy of Maryland, College Park, 2002.
142. A. K. Roy-Chowdhury and R. Chellappa, A factorization approach for event recognition. In CVPR Event Mining Workshop, 2003.
143. A. K. Roy-Chowdhury and R. Chellappa, Stochastic approximation and rate-distortion analysis for robust structure and motion estimation. Int. J. Comput. Vis., 55(1):27-53, Oct. 2003. doi:0.1023/A:1024488407740
144. A.K.Roy-ChowdhuryandR.Chellappa,Aninformationtheoreticcriterion for evaluating the quality of 3D reconstructions from video. IEEE Trans. Image Process., 13(7):960-973, July 2004. doi: 10.1109/TIP.2004.827240
145. A. K. Roy-Chowdhury and R. Chellappa, Face reconstruction from monocular video using uncertainty analysis and a generic model. Comput. Vis. Image Understand., 91:188-213, July 2003. doi:10.1016/S1077-3142(03)00079-1
146. H. Schneiderman and T. Kanade, Probabilistic modelling of local appearance and spatial reationships for object recognition. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2000, pp. 746-751.
147. W. I. Scholhorn, B.M. Nigg, D. J. Stephanshyn, and W. Liu, Identification of individual walking patterns using time discrete and time continuous data sets. Gait Posture, 15:180-186, 2002. doi:1016/S0966-6362(01)00193-X
148. G. Shaffer, A Mathematical Theory of Evidence. Princeton, NJ: Princeton University Press, 1976.
149. Y. Shan, Z. Liu, and Z. Zhang, Model-based bundle adjustment with application to face modeling. In Proc. Int. Conf. Comput. Vis., 2001, pp. 644-651.
150. A. Shashua, Geometry and photometry in 3D visual recognition. Ph.D. Thesis, MIT, 1994.
151. A Shashua, On photometric issues in 3D visual recognition from a single 2d image. Int. J. Comput. Vis., 21:99-122, 1997. doi:10.1023/A:1007975506780
152. I. Shimshoni, Y. Moses, and M. Lindenbaum, Shape reconstruction of 3D bilaterally symmetric surfaces. Int. J. Comput. Vis., 39:97-100, 2000. 10.1023/A:1008118909580
153. H. Sidenbladh, Michael J. Black, and David J. Fleet, Stochastic tracking of 3D human figures using 2D image motion. In Proc. Eur. Conf. Comput. Vis., 2000, pp. 702-718.
154. T. Sim, S. Baker, and M.Bsat, The CMU pose, illumination, and expression (PIE) database. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 2002, pp. 46-51.
155. S. Soatto, G. Doretto, and Y.N. Wu, Dynamic textures. In Proc. Int. Conf. Comput. Vis., Vol. 2, 2001, pp. 439-446.
156. S. Soatto and A.J. Yezzi, Deformotion: Deforming motion, shape average and the joint registration and segmentation of images. In Proc. Euro. Conf. Comput. Vis., III: 32 ff, 2002.
157. S. Srinivasan, Extracting structure from optical flow using fast error search technique. Int. J. Comput. Vis., 37:203-230, 2000. doi:10.1023/A: 1008111923880
158. T. Starner, J. Weaver, and A. Pentland, Real-time American sign language recognition from video using hmms. IEEE Trans. Pattern Anal. Machine Intell., 12(8):1371-1375, Dec. 1998. doi:10.1109/34.735811
159. J. Steffens, E. Elagin, and H. Neven, Personspotter - Fast and robust system for human detection, tracking and recognition. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 1998, pp. 516-521.
160. S. V. Stevenage, M. S. Nixon, and K. Vince, Visual analysis of gait as a cue to identity. Appl. Cogn. Psychol., 13:513-526, March 1999. doi:10.1002/(SICI)1099-0720(199912)13:6<513::AID-ACP616>3.0.CO;2-8
161. J. Strom, T. Jebara, S. Basu, and A.P. Pentland, Real time tracking and modeling of faces: An EKF-based analysis by synthesis approach. In Vismod, 1999.
162. A. Sundaresan, A. K. Roy-Chowdhury, and R. Chellappa, A hidden Markov model based framework for recognition of humans from gait sequences. In Proc. Int. Conf. Image Process., Sept. 2003.
163. A. Sundaresan, A. K. Roy-Chowdhury, and R. Chellappa, Multi-view tracking of human motion modeled by kinematic chains. In Proc. Int. Conf. Image Process., 2004.
164. K. Sung and T. Poggio, Example-based learning for view-based human face detection. IEEE Trans. Pattern Anal. Machine Intell., 20:39-51, Jan. 1997. doi:10.1109/34.655648
165. D.L. Swets and J. Weng, Discriminant analysis and eigenspace partition tree for face and object recognition from views. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 1996, pp. 192-197.
166. D.L. Swets and J.J. Weng, Using discriminant eigenfeatures for image retrieval. IEEE Trans. Pattern Anal. Machine Intell., 18:831-836, Aug. 1996. doi:10.1109/34.5318021
167. R. Tanawongsuwan and A.F. Bobick, Gait recognition from time-normalized joint-angle trajectories in the walking plane. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2001, pp. 726-731.
168. D. Terzopoulos and K. Waters, Analysis and synthesis of facial image sequences using physical and anatomical models. IEEE Trans. Pattern Anal. Machine Intell., 15:569-579, June 1993. doi:10.1109/34.216726
169. D. Tolliver and R. Collins, Gait shape estimation for identification. In Proc. Int. Conf. Audio, Video Biometric Person Authentication, 2003, pp. 734-742.
170. C. Tomasi and T. Kanade, Shape and motion from image streams under orthography: A factorization method. Int. J. Comput. Vis., 9:137-154, Nov. 1992. doi:10.1007/BF00129684
171. L. Torresani and C. Bregler, Space-time tracking. In Proc. Eur. Conf. Comput. Vis., I: 801 ff, 2002.
172. S. Tsuji, A. Morizono, and S. Kuroda, Understanding a simple cartoon film by a computer vision system. In Proc. Int. Joint Conf. AI, 1977, pp. 609-610.
173. M. Turk and A. Pentland, Eigenfaces for recognition. J. Cogn. Neurosci., 3:72-86, 1991.
174. V.N. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
175. N. Vaswani, A. R. Chowdhury, and R. Chellappa, Statistical shape theory for activity modeling. In Proc. Int. Conf. Acoustics, Speech Signal Process., 2003.
176. N. Vaswani, A. R. Chowdhury, and R. Chellappa, Activity recognition using the dynamics of the configuration of interacting objects. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2003, pp. 633-640.
177. N. Vaswani, A. R. Chowdhury, and R. Chellappa, Shape activity: A continuous state hmm for moving/deforming shapes with application to abnormal activity detection. IEEE Trans. Image Process., to be published.
178. A. Veeraraghavan, A. R. Chowdhury, and R. Chellappa, Role of shape and kinematics in human movement analysis. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2004.
179. V.T. Vu, F. Bremond, and M. Thonnat, Automatic video interpretation: A recognition algorithm for temporal scenarios based on pre-compiled scenario models. In CVS03, 2003, p. 523.
180. R. Walter, Principles of Mathematical Analysis, 3rd ed. New York: McGraw-Hill, 1976.
181. H. Wechsler, V. Kakkad, J. Huang, S. Gutta, and V. Chen, Automatic video-based person authentication using the RBF network. In Proc. Int. Conf. Audio, Video Biometric Person Authentication, 1997, pp. 85-92.
182. J. Wilder, Face recognition using transform coding of gray scale projection and the neural tree network. In Artificial Neural Networks with Applications in Speech and Vision, R.J. Mammone, Ed. New York: Chapman Hall, 1994, pp.520-536.
183. A. Wilson and A Bobick, Recognition and interpretation of parametric gesture. In Proc. Int. Conf. Comput. Vis., 1998, pp. 329-336.
184. L. Wiskott, J. M Fellous, and C. von der Malsburg, Face recognition by elastic bunch graph matching. IEEE Trans. Pattern Anal. Machine Intell., 19:775-779, 1997. doi:10.1109/34.598235
185. M. Yamamoto and K. Koshikawa, Human motion analysis based on a robot arm model. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1991, pp. 664-665.
186. M. Yamamoto, A. Sato, S. Kawada, T. Kondo, and Y. Osaki, Incremental tracking of human actions from multiple views. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 1998, pp. 2-7.
187. G.S. Young and R. Chellappa, Statistical analysis of inherent ambiguities in recovering 3D motion from a noisy flow field. IEEE Trans. Pattern Anal. Machine Intell., 14:995-1013, Oct. 1992. doi:10.1109/34.159903
188. A. L. Yuille, D. Snow, Epstein R., and P. N. Belhumeur, Determining generative models of objects under varying illumination: Shape and albedo from multiple images using svd and integrability. Int. J., Comput. Vis., 35:203-222, 1999. doi:10.1023/A:10081807263171
189. A.L. Yuille, D.S. Cohen, and P.W. Hallinan, Feature extraction from faces using deformable templates. Int. J. Comput. Vis., 8:99-111, Aug. 1992. doi:10.1007/BF00127169
190. L. Zhao, Dressed human modeling, detection, and parts localization. Ph.D. Thesis, CMU, 2001.
191. W. Zhao, Robust image based 3D face recognition. Ph.D. Thesis, University of Maryland, 1999.
192. W. Zhao and R. Chellappa, Symmetric shape from shading using self-ratio image. Int. J. Comput. Vis., 45:55-752, 2001. doi:10.1023/A:1012369907247
193. W. Zhao, R. Chellappa, and A. Krishnaswamy, Discriminant analysis of principal components for face recognition. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., 1998, pp. 336-341.
194. W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld, Face recognition: A literature survey. ACM Trans., 35:399-458, Dec. 2003.
195. S. Zhou and R. Chellappa, Illuminating light field: Image-based face recognition across illuminations and poses. In Proc. IEEE Int. Conf. Automatic Face Gesture Recogn., May 2004.
196. S. Zhou and R. Chellappa, Image-based face recognition under illumination and pose variation. J. Opt. Soc. Amer. A, 22:217-229, Feb. 2005, submitted for publication.
197. S. Zhou and R. Chellappa, Multiple-exemplar discriminant analysis for face recognition. In Proc. of Intl. Conf. Pattern Recogn., Aug. 2004.
198. S. Zhou, R. Chellappa, and D. Jacobs, Characterization of human faces under illumination variations using rank, integrability, and symmetry constraints. In Eur. Conf. Comput. Vis., May 2004, pp. 588-601.
199. S. Zhou, V. Krueger, and R. Chellappa, Probabilistic recognition of human faces from video. Comput. Vis. Image Understand., 91:214-245, July-Aug. 2003. doi:10.1016/S1077-3142(03)00080-8