Multichannel and multimodality person identification

Ming Liu, Yanxiang Chen, Xi Zhou, Xiaodan Zhuang, Mark Hasegawa-Johnson, Thomas Huang

Research output: Contribution to journalConference articlepeer-review


Person's identity is a very important high level information for video analysis and retrieval. Along the growth of multimedia data, the recording is not only multimodality and also multichannel(microphone array, camera array). In this paper, we describe a multimodal person identification system of UIUC team for CLEAR 2007 evaluation. The audio only system is based on a new proposed model - Chain of Gaussian Mixtures. The visual only system is a face recognition module based on nearest neighbor classifier at appearance space. Final system fuses 7 channel microphone recordings and 4 camera recordings at decision level. The experimental results indicate the effectiviness of speaker modeling methods and the fusion scheme.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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