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Incremental learning of patch-based bag of facial words representation for online face recognition in videos

  • Chao Wang*
  • , Yunhong Wang
  • , Zhaoxiang Zhang
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Video-based face recognition is a fundamental topic in image and video analysis, and presents various challenges and opportunities. In this paper, we introduce an incremental learning approach to video-based face recognition, which efficiently exploits the spatiotemporal information in videos. Face image sequences are incrementally clustered based on their descriptors. With the quantization of the facial words, representation of the face image is generated by concatenating the histograms from regions. In the online recognition, a temporal matrix and a voting algorithm are employed to judge a face video's identity. The proposed method achieves a 100% recognition rate performed on the Honda/UCSD database, and gives near realtime feedback. Experimental results demonstrate the effectiveness and flexibility of our proposed method.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing, PCM 2012 - 13th Pacific-Rim Conference on Multimedia, Proceedings
Pages1-9
Number of pages9
DOIs
StatePublished - 2012
Event13th Pacific-Rim Conference on Multimedia, PCM 2012 - Singapore, Singapore
Duration: 4 Dec 20126 Dec 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7674 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Pacific-Rim Conference on Multimedia, PCM 2012
Country/TerritorySingapore
CitySingapore
Period4/12/126/12/12

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