Reference-Based Pose-Robust Face Recognition



Despite recent advancement in face recognition technology, practical pose-robust face recognition remains a challenge. To meet this challenge, this chapter introduces reference-based similarity where the similarity between a face image and a set of reference individuals (the “reference set”) defines the reference-based descriptor for a face image. Recognition is performed using the reference-based descriptors of probe and gallery images. The dimensionality of the face descriptor generated by the accompanying face recognition algorithm is reduced to the number of individuals in the reference set. The proposed framework is a generalization of previous recognition methods that use indirect similarity and reference-based descriptors. The effectiveness of the proposed algorithm is shown by transforming multiple variations of the standard, yet powerful, local binary patterns descriptor into pose-robust face descriptors. Results are shown on several publicly available face databases. The proposed approach achieves good accuracy as compared to popular state-of-the-art algorithms, and it is computationally efficient due to its compatibility with orthogonal transform based indexing algorithms.


Face Recognition Discrete Cosine Transform Face Image Local Binary Pattern Reference Individual 
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 2016

Authors and Affiliations

  1. 1.Hewlett Packard LabsPalo AltoUSA
  2. 2.BRIC, University of North Carolina at Chapel HillChapel HillUSA
  3. 3.CRIS, University of CaliforniaRiversideUSA

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