Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition

  • Phalguni Gupta
  • Dakshina Ranjan Kisku
  • Jamuna Kanta Sing
  • Massimo Tistarelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6059)


This paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces.


Face biometrics Graph matching SIFT features Dempster-Shafer decision theory Intra-modal fusion 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Phalguni Gupta
    • 1
  • Dakshina Ranjan Kisku
    • 2
  • Jamuna Kanta Sing
    • 3
  • Massimo Tistarelli
    • 4
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology KanpurKanpurIndia
  2. 2.Department of Computer Science and EngineeringDr. B. C. Roy Engineering College / Jadavpur UniversityDurgapurIndia
  3. 3.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia
  4. 4.Computer Vision Laboratory, DAPUniversity of SassariAlgheroItaly

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