Biometrics and Kansei Engineering by Khalid Saeed (auth.), Khalid Saeed, Tomomasa Nagashima

By Khalid Saeed (auth.), Khalid Saeed, Tomomasa Nagashima (eds.)

Biometrics and Kansei Engineering is the 1st booklet to collect the foundations and purposes of every self-discipline. the way forward for biometrics is wanting new applied sciences which may depend upon people’s feelings and the prediction in their purpose to take an motion. Behavioral biometrics reviews the best way humans stroll, speak, and show their feelings, and Kansei Engineering makes a speciality of interactions among clients, products/services and product psychology. they're turning into relatively complementary.

This e-book additionally introduces biometric functions in the environment, which additional illustrates the shut courting among Biometrics and Kansei Engineering. Examples and case stories are supplied all through this booklet.

Biometrics and Kansei Engineering is designed as a reference publication for pros operating in those similar fields. Advanced-level scholars and researchers learning laptop technology and engineering will locate this publication necessary as a reference or secondary textual content ebook in addition.

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In: Proceedings of IEEE international conference automatic face and gesture recognition, Killington, USA, pp 301–306 39. Atick JJ, Griffin PA, Redlich AN (1996) Statistical approach to shape from shading: reconstruction of 3Dface surfaces from single 2Dimages. Neural Comput 8(6):1321–1340 40. Yan Y, Zhang J (1998) Rotation-invariant 3D recognition for face recognition. In: Proceedings of IEEE international conference image processing, Prague, Czech, vol 1, pp 156–160 41. Zhao WY, Chellappa R (2000) 3D model enhanced face recognition.

IEEE Trans Image Process 11(4):467–476 36. Ahonen T, Hadid A, Pietikainen M (2004) Face recognition with local binary patterns. In: Proceedings of the European conference on computer vision, Prague, Czech, pp 469–481 37. Gordon GG, Lewis ME (1995) Face recognition using video clips and mug shots. In: Proceedings of office of national drug control policy (ONDCP) international technical symposium, Nashua, NH 38. Lengagne R, Tarel JP, Monga O (1996) From 2d images to 3d face geometry. In: Proceedings of IEEE international conference automatic face and gesture recognition, Killington, USA, pp 301–306 39.

The face is divided in two parts, left and right. For each side of the face, we are creating a projection. Obtained function H(y) (see Fig. 8a) is multiplied by function W(y) (see Fig. 8b) in order to minimize the influence of the mouth and nostrils. After multiplication of the H(y) by W(y), we obtain the function shown in Fig. 8c. Maximum value of this function denotes the eye line and the first coordinate of the eye. The second coordinate is calculated by performing adaptive binarization. As a result, we obtain a binary image with the eyes, nostrils, and mouth remaining on it.

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