Thumbnail
Access Restriction
Subscribed

Author del Pozo-Banos, M. ♦ Travieso, C.M. ♦ Alonso, J.B. ♦ Ferrer, M.A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2009
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data ♦ Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword TV ♦ Videos ♦ Face recognition ♦ Face detection ♦ Robustness ♦ Redundancy ♦ Wavelet transforms ♦ Support vector machines ♦ Support vector machine classification ♦ Delay ♦ pattern recognition ♦ Biometric system ♦ face identificatio ♦ face detection ♦ video processing ♦ Support Vector Machines (SVMs)
Abstract Face recognition has been a main object of study, producing robust systems with high reliability. However, these systems face the inconvenience of long processing times which are, in many cases, unwanted. This paper presents a simple face recognition approach from TV video files based on the redundancy of information and a face recognition system used in regular face pictures. More precisely, the model relies on the Wavelet Transform for parameterize faces and Support Vector Machines in order to classify them. After some experiments, the model has shown perfect accuracy in subject detection and recognition, with maximum delay of around 2 seconds.
Description Author affiliation: Department of Señales y Comunicaciones, University of Las Palmas de Gran Canaria. CeTIC- ULPGC., SPAIN. (del Pozo-Banos, M.; Travieso, C.M.; Alonso, J.B.; Ferrer, M.A.)
ISBN 9781424441693
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2009-10-05
Publisher Place Switzerland
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 524.23 kB
Page Count 7
Starting Page 119
Ending Page 125


Source: IEEE Xplore Digital Library