Advances in Face Image Analysis: Techniques and Technologies by Yu-Jin Zhang

By Yu-Jin Zhang

Video and photograph research of the human face presents a wealth of data in regards to the person, , together with age, habit, well-being and career. With learn regularly being performed into a number of purposes of this box, a entire and unique quantity of the hot developments of face snapshot research is favourite. Advances in face snapshot research: suggestions and applied sciences fulfills this want, reviewing and surveying new forward-thinking study and improvement in face photo research applied sciences. With greater than 30 best specialists from around the globe supplying accomplished insurance of assorted branches of face snapshot research, this ebook is a worthwhile asset for college students, researchers and practitioners engaged within the learn, learn and improvement of face photo research thoughts.

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This method is better than many others in terms of recognition rate. The reverse of the medal is the non-trivial computational cost of the training phase. As for robustness to lighting variations in purely 2D methods, the present trend is to exploit some image normalization technique, rather than devising distortion invariant recognition techniques. A comparison is performed in (Ruiz-del-Solar, & Quinteros, 2008) among many lighting normalization algorithms. SQI (Self Quotient Image) (Wang, 2004a) and Local Binary Pattern (Ahoen, 2004), result to represent the best compromise in terms of simplicity, speed and authentication accuracy when the adopted classifier is of eigen-space based type.

Other strategies can make the recognition robust to local alterations. Bartlett et al. (Bartlett, 2002) show that first and second order statistics (PCA) only hold information about the amplitude spectrum of an image, and discard the phase spectrum. However, human object recognition capability appears to be mainly driven by the phase-spectrum. Therefore Independent Component Analysis (ICA) is introduced (Bartlett, 2002) as a more powerful face classification tool. The ICA generalizes PCA, yet providing a better characterization of data, and capturing discriminant features also considering Face Searching in Large Databases the high-order statistics.

Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Trans. PAMI, 12, 103–108. Kramer, M. A. (1991). Nonlinear principal components analysis using auto-associative neural networks. AIChE Journal. American Institute of Chemical Engineers, 32(2), 233–243. , Zhang, J. , & Xie, L. (2008). Developments and applications of nonlinear principal component analysis - A review. Lecture Notes in Computational Science and Engineering, 58, 1–43. , & Taguchi, T. (2005). A kernel-based Fisher discriminant analysis for face detection.

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