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dc.contributor.authorKao, Wen-Chungen_US
dc.contributor.authorShen, Chia-Pingen_US
dc.contributor.authorKao, Chih-Chungen_US
dc.contributor.authorHsu, Ming-Chaien_US
dc.contributor.authorWu, Hung-Hsinen_US
dc.date.accessioned2017-04-21T06:49:11Z-
dc.date.available2017-04-21T06:49:11Z-
dc.date.issued2007en_US
dc.identifier.isbn978-1-4244-0990-7en_US
dc.identifier.issn1062-922Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/135133-
dc.description.abstractReal-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.en_US
dc.language.isoen_USen_US
dc.titleAdaptive feature selection for real-time face recognition in portable surveillance systemsen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2007 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-8en_US
dc.citation.spage2056en_US
dc.citation.epage+en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000255016302006en_US
dc.citation.woscount0en_US
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