Elastic block set reconstruction for face recognition

Dong Li, Xudong Xie, Kin Man Lam, Zhigang Jin

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


In this paper, a novel face recognition algorithm named elastic block set reconstruction (EBSR) is proposed. In our method, the EBSR face is used to represent a set of training faces and to simulate different factors in a query image. An EBSR face is constructed by using the blocks from the training face images which best match to the blocks of the query image at the corresponding locations. The elastic local reconstruction (ELR) error is then used to evaluate how well a block pair matches, and the query image is classified based on the accumulated reconstruction error. The proposed method can effectively explore local information in the training set and deal with various conditions well. Also, the reconstruction error can be considered as a kind of dissimilarity measure, which gives a new approach to designing the training set so as to maximize robustness of recognition. Experiments show that consistent and promising results are obtained.
Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)9781424456543
Publication statusPublished - 1 Jan 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 7 Nov 200910 Nov 2009


Conference2009 IEEE International Conference on Image Processing, ICIP 2009


  • Elastic block set reconstruction (EBSR)
  • Elastic local reconstruction (ELR)
  • Face recognition

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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