An efficient video retrieval scheme based on facial signatures

Pengyi Hao, Sei Ichiro Kamata

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

Abstract

The topic of retrieving videos containing a desired person by just using facial content has many applications like video surveillance, social network, etc. In this paper, we propose a compact, discriminative and low-dimensional signature to describe an person with a set of high-dimensional features. The signature is generated by linear discriminant analysis with maximum correntropy criterion that is robust to outliers and noises. Based on the proposed signatures, a new video retrieval scheme is given for fast finding the desired videos by measuring the similarities between the signature of a query and the ones in the dataset. Evaluations on a large dataset of videos show that the proposed video retrieval scheme has the potential to substantially reduce the response time and slightly increase the mean average precision of retrieval.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Pages2699-2703
Number of pages5
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: 2013 Sep 152013 Sep 18

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
CountryAustralia
CityMelbourne, VIC
Period13/9/1513/9/18

Keywords

  • Linear discriminant analysis
  • Signature
  • Video retrieval

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Hao, P., & Kamata, S. I. (2013). An efficient video retrieval scheme based on facial signatures. In 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings (pp. 2699-2703). [6738556] (2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings). https://doi.org/10.1109/ICIP.2013.6738556