Adaptive feature selection for real-time face recognition in portable surveillance systems

Wen Chung Kao, Chia Ping Shen, Chin Chung Kao, Ming Chai Hsu, Hung Hsin Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Real-time face recognition is a necessary feature in advanced portable surveillance systems. However, the high complexity of available algorithms to objects segmentation and recognition makes it impossible to include such a feature into a portable device. In this paper, we aim at designing a portable surveillance system which can take MPEG audio/video currently with recognizing human faces based on a digital camera platform. The proposed flow fully utilizes the available intermediate data passing from standard video compression flow in a digital camera. An efficient face recognition approach based on adaptive feature extraction and support vector machines (SVMs) are proposed to address the performance issues. The experimental result shows that the recognition speed running on a commercial digital camera platform can achieve 1.216 seconds/frame.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
Pages1083-1087
Number of pages5
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada
Duration: 2007 Oct 72007 Oct 10

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Other

Other2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
CountryCanada
CityMontreal, QC
Period07/10/707/10/10

ASJC Scopus subject areas

  • Engineering(all)

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