2D-LPI: Two-Dimensional Locality Preserving Indexing

  • S. Manjunath
  • D. S. Guru
  • M. G. Suraj
  • R. Dinesh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)


In this paper, we present a new model called two-dimensional locality preserving indexing (2D-LPI) for image recognition. The proposed model gives a new dimension to the conventional locality preserving indexing (LPI). Unlike the conventional method the proposed method can be applied directly on images in 2D plane. In order to corroborate the efficacy of the proposed method extensive experimentation has been carried out on various domains such as video summarization, face recognition and fingerspelling recognition. In video summarization we comapre the proposed method only with 2D-LPP which was recently used for video summarization. In face recognition and fingerspelling recognition we compare the proposed method with the conventional LPI and also with the existing two-dimensional subspace methods viz., 2D-PCA, 2D-FLD and 2D-LPP.


Face Recognition Latent Semantic Analysis Latent Semantic Indexing Video Summarization Locality Preserve Projection 
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-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • S. Manjunath
    • 1
  • D. S. Guru
    • 1
  • M. G. Suraj
    • 1
  • R. Dinesh
    • 2
  1. 1.Department of Studies in Computer ScienceUniversity of MysoreMysoreIndia
  2. 2.Honeywell Technology SolutionsBengaluruIndia

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