Face recognition using elastic local reconstruction based on a single face image

Xudong Xie, Kin Man Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)


In this paper, we propose a new face recognition algorithm based on a single frontal-view image for each face subject, which considers the effect of the face manifold structure. To compare two near-frontal face images, each face is considered a combination of a sequence of local image blocks. Each of the image blocks of one image can be reconstructed according to the corresponding local image block of the other face image. Then an elastic local reconstruction (ELR) method is proposed to measure the similarities between the image block pairs in order to measure the difference between the two face images. Our algorithm not only benefits from the face manifold structure, in terms of being robust to various image variations, but also is computationally simple because there is no need to build the face manifold. We evaluate the performance of our proposed face recognition algorithm with the use of different databases, which are produced under various conditions, e.g. lightings, expressions, perspectives, with/without glasses and occlusions. Consistent and promising experimental results were obtained, which show that our algorithm can greatly improve the recognition rates under all the different conditions.
Original languageEnglish
Pages (from-to)406-417
Number of pages12
JournalPattern Recognition
Issue number1
Publication statusPublished - 1 Jan 2008


  • Elastic local reconstruction (ELR)
  • Expression variations
  • Face manifold structure
  • Face recognition
  • Illumination variations

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering


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