By Khalid Saeed (auth.), Khalid Saeed, Tomomasa Nagashima (eds.)
Biometrics and Kansei Engineering is the 1st publication to assemble the rules and purposes of every self-discipline. the way forward for biometrics is wanting new applied sciences that could rely on people’s feelings and the prediction in their goal to take an motion. Behavioral biometrics reports the way in which humans stroll, speak, and show their feelings, and Kansei Engineering makes a speciality of interactions among clients, products/services and product psychology. they're changing into fairly complementary.
This ebook additionally introduces biometric functions in our surroundings, which additional illustrates the shut dating among Biometrics and Kansei Engineering. Examples and case reviews are supplied all through this e-book.
Biometrics and Kansei Engineering is designed as a reference publication for pros operating in those comparable fields. Advanced-level scholars and researchers learning desktop technological know-how and engineering will locate this ebook helpful as a reference or secondary textual content ebook besides.
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IEEE Trans Pattern Anal Mach Intell 28(12):1302–1319 23. Prabhakar S, Pankanti S, Jain AK (2003) Biometric recognition: security and privacy concerns. IEEE Mag Secur Privacy 1(2):33–42. 1193209 24. Wilson C (2010) Vein pattern recognition: a privacy-enhancing biometric. CRC Press, Boca Raton 25. Kelkboom EJC, Molina GG, Breebaart J, Veldhuis RNJ, Kevenaar TAM, Jonker W (2010) Binary biometrics: an analytic framework to estimate the performance curves under Gaussian assumption. IEEE Trans Syst Man Cybern A: Syst Humans 40(3):555–571 26.
39] proposed a reconstruction method of 3D face surfaces based on the Karhonen-Loeve (KL) transform and the shape-from-shading approach. They also discussed the possibility of using eigenhead surface face recognition applications. , rotation invariant. Zhao and Chellappa  proposed a method to adapt a 3D model from a generic range map to the shape obtained from shading for enhancing face recognition performance in different lighting and viewing conditions. A large number of local features can be produced with varying parameters in the position, scale, and orientation of the filters.
Intensive work is done on removing the possibly existing drawbacks or undesired features in these and other algorithms. This would definitely result in improving the algorithmic level of performance and their operation time for faster, productive action and universal applications. Acknowledgment This work was partially supported by AGH University of Science and Technology in Cracow, grant no. 01. References 1. Schneier B (1999) Inside risks: the uses and abuses of biometrics. Commun ACM 42(8):136 2.