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Browsing a Large Collection of Community Photos Based on Similarity on GPU

  • Grant Strong
  • Minglun Gong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5359)

Abstract

A novel approach is proposed in this paper to facilitate browsing a large collection of community photos based on visual similarities. Using extracted feature vectors, the approach maps photos onto a 2D rectangular area such that the ones with similar features are close to each other. When a user browses the collection, a subset of photos is automatically selected to compose a photo collage. Once having identified photos of interest the user can find more photos with similar features through panning and zooming operations, which dynamically update the photo collage. To quickly organize a large number of photos, the 2D mapping process is performed on the GPU, which yields 15~19 times speedup over the CPU implementation.

Keywords

Feature Vector Graphic Processing Unit Image Retrieval Neighborhood Size Relevance Feedback 
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 2008

Authors and Affiliations

  • Grant Strong
    • 1
  • Minglun Gong
    • 1
  1. 1.Department of Computer ScienceMemorial University of NewfoundlandCanada

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