Keypoints Derivation for Object Class Detection with SIFT Algorithm

  • Krzysztof Slot
  • Hyongsuk Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)


The following paper proposes a procedure for SIFT keypoints derivation for the purpose of object class detection. The main idea of the method is to build appropriate object class keypoints by extracting information that corresponds to characteristic class features. The proposed procedure is composed of two main steps: clustering of similar SIFT keypoints and derivation of appropriate keypoint descriptors. Face detection in images has been selected as a sample application for the proposed approach performance evaluation.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Krzysztof Slot
    • 1
  • Hyongsuk Kim
    • 2
  1. 1.Lodz and Academy of Humanities and EconomicsInstitute of Electronics, Technical University of LodzLodzPoland
  2. 2.Division of Electronics and Information EngineeringChonbuk National UniversityChonjuRepublic of Korea

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