Efficient face recognition system based on luminance distribution by using maximum likelihood
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[1] V. K. Chadda,et al. A Multi-Algorithmic Face Recognition System , 2006, 2006 International Conference on Advanced Computing and Communications.
[2] Geovanni Martinez,et al. Maximum-likelihood motion estimation of a human face , 2003, ICME.
[3] Itu-T and Iso Iec Jtc. Advanced video coding for generic audiovisual services , 2010 .
[4] S. Neogy,et al. A Low Overhead Checkpointing Scheme for Mobile Computing Systems , 2007, 15th International Conference on Advanced Computing and Communications (ADCOM 2007).
[5] Iso/iec 14496-2 Information Technology — Coding of Audio-visual Objects — Part 2: Visual , 2022 .
[6] 三田 真弓,et al. ISO/IEC JTC 1 : 情報技術の国際標準化組織 , 1996 .
[7] Itu-T. Video coding for low bitrate communication , 1996 .
[8] Qingchuan Tao,et al. Face Recognition using new image representations , 2009, 2009 International Joint Conference on Neural Networks.
[9] V. P. Vishwakarma,et al. A Novel Approach for Face Recognition Using DCT Coefficients Re-scaling for Illumination Normalization , 2007, 15th International Conference on Advanced Computing and Communications (ADCOM 2007).
[10] Meng Joo Er,et al. High-speed face recognition based on discrete cosine transform and RBF neural networks , 2005, IEEE Transactions on Neural Networks.
[11] Zhihong Zeng,et al. Face localization via hierarchical CONDENSATION with Fisher boosting feature selection , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..