Download e-book for iPad: Advanced Studies in Biometrics: Summer School on Biometrics, by J. Bigun, J. Fierrez-Aguilar, J. Ortega-Garcia, J.

By J. Bigun, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez (auth.), Massimo Tistarelli, Josef Bigun, Enrico Grosso (eds.)

ISBN-10: 3540262040

ISBN-13: 9783540262046

Automatic individual authentication, the identity and verification of somebody as such, has more and more been stated as an important point of assorted safeguard functions. a number of popularity and identity structures were in keeping with biometrics using biometric positive aspects comparable to fingerprint, face, retina scans, iris styles, hand geometry, DNA lines, gait, and others.

This publication originates from a world summer season college on biometrics, held in Alghero, Italy, in June 2003. The seven revised instructional lectures via prime researchers introduce the reader to biometrics-based individual authentication, fingerprint attractiveness, gait attractiveness, quite a few elements of face attractiveness and face detection, topologies for biometric reputation, and hand detection. additionally incorporated are the 4 top chosen scholar papers, all facing face recognition.

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Read Online or Download Advanced Studies in Biometrics: Summer School on Biometrics, Alghero, Italy, June 2-6, 2003. Revised Selected Lectures and Papers PDF

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Extra resources for Advanced Studies in Biometrics: Summer School on Biometrics, Alghero, Italy, June 2-6, 2003. Revised Selected Lectures and Papers

Example text

One problem with some model-based systems is that they are computationally intensive, which makes them either too slow or too expensive for use in a biometric system. Bissacco et al. [53] extend results from acquisition of kinematic pose to recognition. They use Bregler’s method [54] to extract joint angle trajectories from a motion sequence. They then compute an auto-regressive moving-average (ARMA) model of the joint movement which they in turn use as a feature vector for recognition. Their system can recognize different types of gaits such as running, walking, or walking a staircase.

In order to facilitate matching, the raw digital representation is usually further processed by a feature ex1 Portions reprinted from: D. Maltoni, D. K. Jain and S. Prabhakar, “Handbook of Fingerprint Recognition,” Springer, 2003. 2003 Springer. M. Tistarelli, J. Bigun, and E. ): Biometrics School 2003, LNCS 3161, pp. 43-68, 2005.  Springer-Verlag Berlin Heidelberg 2005 44 D. Maltoni tractor to generate a compact but expressive representation, called a template. The verification task is responsible for verifying individuals at the point of access.

They use Bregler’s method [54] to extract joint angle trajectories from a motion sequence. They then compute an auto-regressive moving-average (ARMA) model of the joint movement which they in turn use as a feature vector for recognition. Their system can recognize different types of gaits such as running, walking, or walking a staircase. Although they did not test it for biometric gait recognition, this remains as a possibility. 7 Other Applications Although the subject of this volume is biometrics, we feel it is worth noting some of the other applications that are related to biometric gait analysis.

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Advanced Studies in Biometrics: Summer School on Biometrics, Alghero, Italy, June 2-6, 2003. Revised Selected Lectures and Papers by J. Bigun, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez (auth.), Massimo Tistarelli, Josef Bigun, Enrico Grosso (eds.)


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