Face Recognition with Image Misalignment via Structure Constraint Coding

  • Ying Tai
  • Jianjun Qian
  • Jian YangEmail author
  • Zhong Jin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9010)


Face recognition (FR) via sparse representation has been widely studied in the past several years. Recently many sparse representation based face recognition methods with simultaneous misalignment were proposed and showed interesting results. In this paper, we present a novel method called structure constraint coding (SCC) for face recognition with image misalignment. Unlike those sparse representation based methods, our method does image alignment and image representation via structure constraint based regression simultaneously. Here, we use the nuclear norm as a structure constraint criterion to characterize the error image. Compared with the sparse representation based methods, SCC is more robust for dealing with illumination variations and structural noise (especially block occlusion). Experimental results on public face databases verify the effectiveness of our method.


Face Recognition Face Image Training Image Sparse Representation Query Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringNanjing University of Science and TechnologyNanjingChina

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