International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 7, No. 5, 8 May 2015
Cover page and Table of Contents: PDF (size: 482KB)
Face Recognition in Multi Camera Network with Sh Feature
Full Text (PDF, 482KB), PP.59-64
Views: 0 Downloads: 0
Author(s)
R.Sumathy
1,*
Index Terms
Face recognition, still image based, video based face recognition, multi view recognition, particle filter and spherical harmonics
Abstract
Multi view face recognition using multiple camera networks is an active research area. The main aim of this paper is to handle different pose variations in multi camera network and recognizing face from those videos. The traditional approaches handle the pose estimation explicitly ,the proposed work will handle the multiple views of the poses .For a given set of multi view video sequences we use particle filter to track the 3D location of the head. The texture map is generated by back projecting the multi view video. The proposed work is developed using the Spherical Harmonic (SH) representation of the face from the texture mapped on to the sphere. A robust feature is constructed based on the properties of SH projection.
Cite This Paper
R.Sumathy, "Face Recognition in Multi Camera Network with Sh Feature", International Journal of Modern Education and Computer Science (IJMECS), vol.7, no.5, pp.59-64, 2015. DOI:10.5815/ijmecs.2015.05.08
Reference
[1]S.Ba, J.M.Odobez “Probabilistic head pose tracking evaluation in single and multiple camera set ups”, Multimodal Techno. Perception Humans, vol 4625, pp.276-286, June 2008.
[2]Q.Cai, A.C.Sankaranarayanan, Q.Zhang, Z.Zhang, z.Liu “Real time head pose tracking from multiple camera with generic model” in Proc. CVPR Workshops, pp.25-32 June 2010.
[3]JangI.Y., LeeK.H. Depth” Video based human model reconstruction resolving self‐occlusion” IEEE Transactionson Consumer Electronics, 2010, 56(3): 1933‐1941.
[4]Wen Yi zho, Rama Chellapa “Image based face recognition issues and methods”, IEEE transactions 1997.
[5]Yongbin Zhang, Aleix M. Martıńez “A weighted probabilistic approach to face recognition from multiple images and video sequences” Elsevier August 2005.
[6]David Beymer Tomaso Poggio “Face recognition from one example view” Massachusetts Institutue of Technology,Sep 1995.
[7]Zhimin Cao, Qi Yin, Xiaoou Tang, Jian Sun “Face Recognition with Learning-based Descriptor” Computer Vision and Pattern Recognition (CVPR), IEEE Conference June 2010.
[8]Chen Lu, Yang Jie “Automatic 3D Face Model Reconstruction Using One Image” Advances in Machine Vision, Image Processing, and Pattern Analysis Lecture Notes in Computer Science Volume 4153, Springer 2006, pp 235-243.
[9]S. Zhou, V. Krueger, and R. Chellappa. “Probabilistic recognition of human faces from video” Computer Vision and Image Understanding, 91:214–245, July-August 2003.
[10]Ke Lu, Zhengming Ding, Jidong Zhao, Yue Wu “Video-based face recognition”IEEE Image and Signal Processing (CISP), 2010 3rd International Congress on (Volume: 1) Oct. 2010.
[11]Zhen Lei, Chao Wang, Qinghai Wang, Yanyan Huang, “Real-Time Face Detection and Recognition for Video Surveillance Applications” Computer Science and Information Engineering, 2009 WRI World Congress on (Volume: 5), April 2 2009.
[12]Ping Zhang, Lorman,”A video-based face detection and recognition system using cascade face verification modules” IEEE MS Applied Imagery Pattern Recognition Workshop, AIPR, Oct. 2008.
[13]Xiaoming Liu; Tsuhan Chen “Video-based face recognition using adaptive hidden Markov models”, Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on (Volume: 1) June 2003.
[14]Stallkamp, Ekenel, H.K.; Stiefelhagen, J. “Video-based Face Recognition on Real-World Data”. Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on Oct. 2007.
[15]Aggarwal, G.; Chowdhury, A.K.R.; Chellappa, R. “A system identification approach for video-based face recognition” Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference(vol 4)Aug 2004.
[16]A.Pnevmatikakis, L.Polymenakos, “video –to-video face recognition”, Far field Intech Chennai 2007,pp.468-486.
[17]20. K.Ramnath, S.Koterba, J.Xiao, C.Hu, I.Mathews, s.Baker “Multi view AAM fitting and construction”, International .Journal of Computer Vision Vol 76, PP.183-204, Feb 2008.
[18]X.Liu, T.Chen “Pose –robust face recognition using geometry assisted probabilistic modeling” IEEE Conference Computer Vision Pattern Recognition, vol 1 pp.502-509, June 2005.
[19]R. E. Kalman “A new approach to linear filtering and prediction problems” Transactions of the ASME – Journal of Basic Engineering, No. 82 (Series D). (1960), pp. 35-45.
[20]Olfati-Saber, R., Fax, J. A., Murray, R. M. (2007). “Consensus and cooperation in networked multi-agent systems.” Proceedings of the IEEE, pp.215–233.