Video-based Face Recognition: A Survey
Commenced in January 2007
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Edition: International
Paper Count: 32804
Video-based Face Recognition: A Survey

Authors: Huafeng Wang, Yunhong Wang, Yuan Cao

Abstract:

During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered.

Keywords: Face recognition, video-based, survey

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084454

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[1] W.Y. Zhao, R. Chellappa, A. Rosenfeld, P.J. Phillips, Face Recognition: A Literature Survey, ACM Computing Surveys,Vol:35, 2003.
[2] G. Aggarwal, A. R. Chowdhury, R. Chellappa, A system identification approachfor video-based face recognition, in: 17th International Conference on PatternRecognition, Vol. 4, 2004, pp. 175- 178.
[3] B. Moghaddam and A. Pentland, "Probabilistic Visual Learning for Object Representation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 696-710, July 1997.
[4] H.A. Rowley, S. Baluja, and T. Kanade, "Neural Network-Based Face Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 23-38, Jan. 1998.
[5] B. Heisele, T. Poggio, and M. Pontil, "Face Detection in Still Gray Images," A.I. memo AIM-1687, Artificial Intelligence Laboratory, MIT, 2000.
[6] Ti-QiongXu; Bi-Cheng Li; Bo Wang, Face detection and recognition using neural network and hidden Markov models, Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, pp. 228 - 231,2003.
[7] P. Viola and M. Jones, "Rapid Object Detection Using a Boosted Cascade of Simple Features," Proc. Conf. Computer Vision and Pattern Recognition, pp. 511-518, 2001.
[8] R.L. Hsu, M. Abdel-Mottaleb, and A.K. Jain, "Face Detection in Color Images," Proc. Int'l Conf. Image Processing, pp. 1046-1049, 2001.
[9] Z. Liu and Y. Wang, "Face Detection and Tracking in Video Using Dynamic Programming" Proc. Int'l Conf. Image Processing, 2000.
[10] L. Silva, K. Aizawa and M. Hatori. "Detection and Tracking of Facial Features". Proc. Of SPIE Visual Communications and Image Processing, Taiwan. May, 1995.
[11] M. Han, A. Sethi, and Y. Gong. A detection-based multiple object tracking method. In Proc. Int. Conf. Image Process. (ICIP), pages 3065-3068, Singapore, Oct. 2004.
[12] D. Ramanan and D. Forsyth. Using temporal coherence to build models of animals. In Proc. Int. Conf. Comp. Vision(ICCV), pages 338-346, Nice, France, Oct. 2003.
[13] D. Maio and D. Maltoni. Real-time face location on grayscale static images. Pattern Recognition, 33:1525-1539, September 2000.
[14] Mikolajczyk, K.; Choudhury, R.; Schmid, C. ,Face detection in a video sequence-a temporal approach, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol 2, pp: 96-101, 2001.
[15] Zhenqiu Zhang; Potamianos, G.; Ming Liu; Huang, T., Robust Multi-View Multi-Camera Face Detection inside Smart Rooms Using Spatio-Temporal Dynamic Programming, 7th International Conference on Automatic Face and Gesture Recognition, 2-6 April 2006 Page(s):407 - 412.
[16] J. Yang and A.Waibel. A real-time face tracker. In Proceedings of the Third IEEE Workshop on Applications of Computer Vision, pages 142-147, Sarasota, FL, 1996.
[17] G. Bradski. Computer vision face tracking for use in a perceptual user interface. Technical Report Q2, Intel Corporation, Microcomputer Research Lab, Santa Clara, CA, 1998.
[18] H. Schneiderman and T. Kanade. "A statistical method for 3d object detection applied to faces and cars". In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2000.
[19] J. Feraud, O. Bernier, and M. collobert. "A fast and accurate face detector for indexation of face images". In Proc. Fourth IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 52-59, 1998.
[20] S. Gong, S.McKenna, and J.Collins. "An investigation into face pose distribution". In Proc. IEEE International Conference on Face and Gesture Recognition, Vermont,1996.
[21] ZhenQiu Zhang; Long Zhu; Li, S.Z.; HongJiang Zhang,Real-time multi-view face detection, Fifth IEEE International Conference on Automatic Face and Gesture Recognition, pp:142-147,2002.
[22] P. Viola and M.J. Jones, "Robust real-time object detection", IEEE ICCV Workshop on Statistical and Computational Theories of Vision. Vancouver, Canada. July 13, 2001.
[23] S. Z. Li, Z. Q. Zhang, "FloatBoost Learning and Statistical Face Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 26, NO. 9, September, 2004.
[24] Yan Wang; Yanghua Liu; Linmi Tao; Guangyou Xu ,Real-time multi-view face detection and pose estimation in video stream, 18th International Conference on Pattern Recognition ,pp: 354 - 357,2006.
[25] M. Nakamura, H. Nomiya and K. Uehara, "Improvement of boosting algorithm by modifying the weighting rule", Annals of Mathematics and Artificial Intelligence, 41:95-109,2004.
[26] C.J. Edward, C.J. Taylor, and T.F. Cootes, "Learning to Identify and Track Faces in an Image Sequence," Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 260-265, 1998.
[27] K. Toyama and A. Blake, "Probabilistic Exemplar Based Tracking in a Metric Space," Proc. Int'l Conf. Computer Vision, vol. 2, pp. 50-57, 2001.
[28] Hongliang Li, King N. Ngan, Saliency model-based face segmentation and tracking in head-and-shoulder video sequences, Visual Communication & Image Representation, 2008,Vol.19(No.5).
[29] G.D. Hager and P.N. Belhumeur, "Efficient Region Tracking with Parametric Models of Geometry and Illumination", IEEE Transactions on Pattern Analyvsis and Machine Intelligence, vol. 20, 1998, pp 1025-1039.
[30] T. Cootes, G. Edwards and C.Taylor, "Active Appearance Models",IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, 2001, pp 681-685.
[31] Ahlberg J ,An Active Model for Facial Feature Tracking EURASIP Journal on Applied Signal Processing 2002,pp: 566-571.
[32] J Saragih, R Goecke, Monocular and Stereo Methods for AAM Learning from Video CVPR '07. IEEE Conference on Computer Vision and Pattern Recognition, pp:1-8,2007.
[33] M. Isard and A. Blake, "Condensation - Condition Density Propagation for Visual Tracking", Int. J. Coo puter Vision, vol. 29, 1998, pp. 5-28.
[34] K.-H. Seo, J-Y. Lee and J.J. Lee, "Adaptive Color Snake Tracker using Condensation Algorithm", IEEE 5th Asian Control Conference, 2004.
[35] Hyung-Soo Lee, Daijin Kim, Robust face tracking by integration of two separate trackers: Skin Color and facial shape, Pattern Recognition 40 (2007) ,pp:3225 - 3235
[36] Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris Samaras, Integration of deformable contours and a multiple hypotheses Fisher color model for robust racking in varying illuminate environments, Image and Vision Computing 25 (2007),pp: 285-296.
[37] Ying Ren, Chin Seng Chua,Bilateral learning for color-based tracking, Image and Vision Computing 26 (2008),pp:1530-1539.
[38] Jwu-Sheng Hu, Chung-Wei Juan, Jyun-Ji Wang,A Spatial-color mean-shift object tracking algorithm with scale and orientation estimation, Pattern Recognition Letters 29 ,2008 pp:2165-2173.
[39] Yan Tong, YangWang, Zhiwei Zhu, Qiang Ji ,Robust facial feature tracking under varying face pose and facial expression, Pattern Recognition 40 (2007), pp: 3195 - 3208.
[40] Tu JL, Tao H, Huang T;Face as mouse through visual face tracking; Computer Vision And Image Understanding; Vol:108(1-2),pp: 35-40, 2007.
[41] Christian Kublbeck, Andreas Ernst, Face detection and tracking in video sequences using the modified census transformation, Image and Vision Computing 24 (2006), pp: 564-572.
[42] Brais Martinez, Xavier Binefa, Piecewise affine kernel tracking for non-planar targets, Pattern Recognition 41 (2008), pp: 3682 - 3691.
[43] Indra Adji Sulistijono, Naoyuki Kubota, Evolutionary Robot Vision and Particle Swarm Optimization for Multiple Human Heads Tracking of A Partner Robot; 2007 IEEE Congress On Evolutionary Computation, Vol:1-10, pp: 1535-1541,2007.
[44] Yonggang Jin, Farzin Mokhtarian Data Fusion for Robust Head Tracking by Particles, Proceedings 2nd Joint IEEE International Workshop on VS-PETS, 2005.
[45] Wenlong Zheng, Suchendra M. Bhandarkar, Face detection and tracking using a Boosted Adaptive Particle Filter, Journal Of Visual Communication And Image Representation; Vol:20(1), pp:9-27,2009.
[46] S. Birchfield, "Elliptical Head Tracking Using Intensity Gradients and Color Histograms," Proc. Conf. Computer Vision and Pattern Recognition, pp. 232-237, 1998.
[47] J. MacCormick and A. Blake, "A Probabilistic Exclusion Principle for Tracking Multiple Objects," Proc. Int'l Conf. Computer Vision, 1995.
[48] Y. Raja, S.J. McKenna, and S. Gong, "Tracking and Segmenting People in Varying Lighting Conditions Using Color," Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 228-233, 1998.
[49] D. Comaniciu, V. Ramesh, and P. Meer. Real-time tracking of non-rigid objects using mean shift. In Proc. of the CVPR, Hilton Head Island, S.C., U.S.A., 2000. Vol. 2, pp. 142-149.
[50] M. Isard and A. Blake, "Condensation-conditional density propagation for visual tracking", Int. Journal, Computer Vision, vol. 29, no. 1, pp. 5-28, 1998.
[51] H. Yao and W. Gao, "Face locating and tracking method based on chroma transform in color images", Signal Processing Proc.2000 , vol 2. pp. 1367-1371, 2000.
[52] F. Huang and T. Chen, "Tracking of multiple faces for human-computer interfaces and virtual environments," Int. Conf. Multimedia, Expo, pp. 1563-1566, vol. 3, 2000.
[53] Terrillon, J.-C.Pilpre, A.Niwa, Y.Yamamoto, K. ; DRUIDE : A Real-Time System for Robust Multiple Face Detection, Tracking and Hand Posture Recognition in Color Video sequences, Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004.
[54] M. L. Cascia and S. Sclaroff. Fast, reliable head tracking under varying illumination. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, Fort Collins, CO,June 1999.
[55] A.J. OToole, D.A. Roark, H. Abdi, Recognizing moving faces: a psychological and neural synthesis, Trends in Cognitive Science 6 (2002) 261-266.
[56] A. Roy Chowdhury, R. Chellappa, R. Krishnamurthy and T.Vo, "3D Face Recostruction from Video Using A Generic Model", In Proc. of Int. Conf. on Multimedia and Expo, Lausanne, Switzerland, August 26-29, 2002.
[57] S. Baker and T. Kanade, "Limits on Super-Resolution and How to Break Them", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 9, September 2002, pp.1167-1183.
[58] X. Liu, T. Chen and S. M. Thornton, "Eigenspace Updating for Non-Stationary Process and Its Application to Face Recognition", To appear in Pattern Recognition, Special issue on Kernel and Subspace Methods for Computer Vision, September 2002.
[59] G. Shakhnarovich, J. W. Fisher, and T. Darrell. Face recognition from long-term observations. In Proc. European Conf. on Computer Vision, volume 3, pp: 851-865, 2002.
[60] W. Y. Zhao and R. Chellappa. Symmetric shape-fromshading using self-ratio image. Int'l. J. Computer Vision, 45(1) pp:55-75, 2001.
[61] Y. Li, S. Gong, and H. Liddell. Constructing facial identity surface in a nonlinear discriminating space. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, volume 2, pp:258-263, 2001.
[62] S. Zhou and R. Chellappa. Probabilistic human recognition from video. In Proc. European Conf. on Computer Vision, volume 3, pp: 681-697, 2002.
[63] Zhang YB, Martinez AM, A weighted probabilistic approach to face recognition from multiple images and video sequence, Image And Vision Computing, Vol 24(6), pp: 626-638,2006.
[64] V. Kr¨ueger and S. Zhou. Exemplar-based face recognition from video. In Proc. European Conf. on Computer Vision, volume 4, pp: 732-746.
[65] Y. Li, T. Wang, and H.-Y. Shum. Motion textures: A two level statistical model for character motion synthesis. In Proc. SIGGRAPH, pp: 465-472, 2002.
[66] Kuang-Chih Lee; Ho, J.; Ming-Hsuan Yang; Kriegman, D., video-based face recognition using probabilistic appearance manifolds, Proceedings. 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 313-320, 2003.
[67] S. Zhou, V. Krueger, R. Chellappa, Face recognition from video: A condensation approach, in: IEEE Int. Conf. on Automatic Face and Gesture Recognition, 2002, pp. 221-228.
[68] Abdenour Hadid; Matti Pietik?inen; Combining appearance and motion for face and gender recognition from videos, Pattern Recognition, Vol:42(11),2009,pp: 2818-2827.
[69] Chellappa, R.; Kruger, V.; Shaohua Zhou, Probabilistic recognition of human faces from video, 2002 International Conference on Image Processing, Vol 1, 2002, pp. 41-45.
[70] S. Satoh. Comparative evaluation of face sequence matching for content-based video access. In IEEE International Conference on Automatic Face & Gesture Recognition, pp:163-168, 2000.
[71] Gregory Shakhnarovich, Baback Moghaddam Face Recognition in Subspaces, Handbook of Face Recognition, 2004.
[72] L. Wolf and A. Shashua. Kernel principal angles for classification machines with applications to image sequence interpretation. In Proc. of Intl. Conf. on Computer Vision and Pattern Recognition, 2003.
[73] Topkaya, I.S.; Bayazit, N.G.; Improving Face Recognition from Video with Preprocessed Representative Faces, 23rd International Symposium on Computer and Information Sciences, 2008. ISCIS '08. Page(s):1 - 4.
[74] Tangelder JWH, Schouten BAM ;Learning a Sparse Representation from Multiple Still Images for online face recognition in an Unconstrained Environment; 18th International Conference on Pattern Recognition, Vol 3, pp: 1087-1090,2006.
[75] Vaswani N, Chellappa R; Principal Components Null Space Analysis for Image and Video Classification; IEEE Transactions on Image Processing, 2006; pp: 1816-1830.
[76] S. Soatto, G. Doretto, Y. Wu, Dynamic textures, in: International Conference on Computer Vision, Vol. 2, Vancouver, BC, Canada, 2001, pp. 439-446.
[77] X. Liu and T. Chen, "Video-based face recognition using adaptive hidden markov models", Proc. IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1: 340-345, 2003.
[78] Minyoung Kim; Kumar, S.; Pavlovic, V.; Rowley, H.; Face Tracking and Recognition with Visual Constraints in Real-World Videos, IEEE Conference on Computer Vision and Pattern Recognition, 2008. CVPR 2008, 23-28 June 2008 Page(s):1 - 8.
[79] C. Shan, S. Gong, P. McOwan, Learning gender from human gaits and faces,IEEE International Conference on Advanced Video and Signal based Surveillance, 2007, pp:505-510.
[80] Zhou X, Bhanu B ;Feature fusion of side face and gait for video-based human identification; Pattern Recognition,Vol:41(3); pp: 778-795,2008.
[81] Christian Micheloni , Sergio Canazza , Gian Luca Foresti; Audio-video biometric recognition for non-collaborative access granting; Visual Languages and Computing,2009.
[82] M. Balasubramanian , S. Palanivela, and V. Ramalingama; Real time face and mouth recognition using radial basis function neural networks; Expert Systems with Applications, Vol:36(3), pp: 6879-6888.
[83] Y Adini, Y Moses, S Ullman," Face recognition: the problem of compensating for changes in illumination direction" ,IEEE Transactions on Pattern Analysis and Machine, Vol.19: 721-732,1997.
[84] WY Zhao, R Chellappa "Illumination-insensitive face recognition using symmetricshape-from-shading" IEEE Conference on Computer Vision and Pattern Recognition, 2000.
[85] PN Belhumeur, JP Hespanha, DJ Kriegman, "Eigenfaces vs. Fisherfaces: recognition using class specific linear projection" IEEE Transactions on pattern analysis and machine, Vol 19:711-720,1997.
[86] Bartlett, M. Stewart, & Sejnowski, T., 1997. Viewpoint invariant face recognition using independent Component analysis and attractor networks. In M. Mozer, M. Jordan, & T. Petsche, Eds.,Advances in Neural Information Processing Systems 9. Cambridge, MA: MIT Press: 817-823.
[87] Chen, W., Er, M. J., & Wu, S.. Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics, 36(2), 458-466,2006.
[88] Jacobs, D. W., Belhumeur, P. N., & Barsi, R.. Comparing images under variable illumination. In Proceedings, IEEE conference on computer vision and pattern recognition pp. 610-617. 1998.
[89] Nanni, L., & Maio, D. Weighted sub-Gabor for face recognition. Pattern Recognition Letters, 28(4), 487-492 2007.
[90] Liu, D. H., Shen, L. S., Lam, K. M., & Kong, X.. Illumination invariant face recognition. Pattern Recognition, 38, 1705-1716.2005.
[91] Wang, H., Li, S. Z., & Wang, Y. Face recognition under varying lighting conditions using self quotient image. In Proceedings of the IEEE international conference on automatic face and gesture recognition pp. 819-824,2004.
[92] Savvides, M., Kumar, B. V., & Khosla, P. K. Corefaces - robust shift invariant PCA based correlation filter for illumination tolerant face recognition. In Proceedings of the international conference on computer vision and pattern recognition Vol. 2, pp. 834-841,2004.
[93] Du, S., & Ward, R. Wavelet based illumination normalization for face recognition. In Proceedings of international conference on image processing Vol. 2, pp. 954-957,2005.
[94] Ojala, T., Pietikainen, M., & Maenpaa, T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7), 971-987. 2002.
[95] Zhang, W., Shan, S., Chen, X., & Gao, W. Are Gabor phases really useless for face recognition? In Proceedings of international conference on pattern recognition Vol. 4, pp. 606-609,2006.
[96] Tan, X., & Triggs, B. Enhanced local texture feature sets for face recognition under difficult lighting conditions. In Proceedings of the IEEE international workshop on analysis and modeling of faces and gestures pp. 168-182.2007.
[97] Georghiades, A., Kriegman, D., & Belhumeur, P. From few to many: Generative models for recognition under variable pose and illumination. IEEE Transactions Pattern Analysis and Machine Intelligence, 40, 643-660. 2001.
[98] T Vetter, T Poggio, Linear object classes and image synthesis from a single example image, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 19: 733-742, 1997.
[99] L. Wiskott, J. Fellous, N. Kruger, and C. V. malsburg. "Face recognition by elastic bunch graph matching". IEEE Transactions on Pattern Analysis and Machine Intelligence,19(7):775-779, 1997.
[100] Freeman, W.T.; Tenenbaum, J.B., Learning bilinear models for two-factor problems in vision, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997, pp. 554 - 560.
[101] T. Cootes, K. Walker, and C. Taylor. View-based active appearance models. In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition, pages 227-232, 2000.
[102] I. Matthews, R. Gross, and S. Baker, Appearance-based face recognition and light-fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 4, pp. 449-465,2004.
[103] M. Everingham and A. Zisserman, Identifying individuals in video by combinig 'generative' and discriminative head models, in Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV '05), vol. 2, pp. 11031110, Beijing,China, October 2005.
[104] O. Arandjelovic, G. Shakhnarovich, J. Fisher, R. Cipolla, and T. Darrell, Face recognition with image sets using manifold density divergence, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '05), vol. 1, pp. 581-588, San Diego, Calif, USA.
[105] O. Arandjelovic and R. Cipolla, An illumination invariant face recognition system for access control using video, in Proceedings of the British Machine Vision Conference (BMVC '04), pp.537-546, Kingston, Canada, September 2004.
[106] Arandjelovic O, Cipolla R A pose-wise linear illumination manifold model for face recognition using video; Computer Vision And Image Understanding,Vol:113(1), pp: 113-125,2009.
[107] Abate AF, Nappi M, Riccio D, et al.; 2D and 3D face recognition: A survey; Pattern Recognition Letters, Vol:28(15),pp: 1885-1906,2007.
[108] V. Blanz, T. Vetter, A morphable model for the syntheses of 3D faces, in: Proceedings of International Conference on Computer Graphics, 1999, pp. 187-194.
[109] C. Zhang, F. Cohen, 3-D face structure extraction and recognition from images using 3-D morphing and distance mapping, IEEE Trans. Image Process. 11 (11) (2002).
[110] Dalong Jiang,Yuxiao Hu, Shuicheng Yan, Lei Zhang, Hongjiang Zhang, Wen Gao, Efficient 3D reconstruction for face recognition, Pattern Recognition 38 (2005), pp:787 - 798
[111] Sotiris Malassiotis, Michael G. Strintzis, Robust face recognition using 2D and 3D data: Pose and illumination compensation, Pattern Recognition 38 (2005) ,pp:2537 - 2548.
[112] Y.Cheng, K.Liu, J.Yang, Y.Zhuang and N.Gu, "Human Face Recogntion Method Based on the Statistical Model of Small Sample Size," in Intelligent Robots and Computer Vision X: Algorithms and Techniques, pp.85-95, 1991.
[113] Arandjelovic O., Cipolla R., Colour invariants for machine face recognition, 8th IEEE International Conference on Automatic Face & Gesture Recognition, 2008. FG '08. pp: 1-8.
[114] Jae Young Choi, Yong Man Ro, Konstantinos N. Plataniotis, Feature Subspace Determination in Video-based Mismatched Face Recognition, 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008).
[115] Xiaoli Zhou; Bhanu B ,Human Recognition Based on Face Profiles in Video, IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. Pp:15.
[116] Tse-Wei Chen, Shou-Chieh Hsu, Shao-Yi Chien, Feature-based Face Scoring in Surveillance Systems, Ninth IEEE International Symposium on Automatic Multimedia, 2007. pp: 139-146.