Image Browsing with PCA-Assisted User-Interaction

  • Authors:
  • Ivo Keller;Thomas Meiers;Thomas Ellerbrock;Thomas Sikora

  • Affiliations:
  • -;-;-;-

  • Venue:
  • CBAIVL '01 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01)
  • Year:
  • 2001

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Abstract

User interfaces for sophisticated search engines mustoffer users a quick and easy access to t e objects to bevisualized. We present a browsing tool, which arrangesimages with respect to the user search intention in a continuous and intuitive manner in real time. Since the capacity of the visual human system is higher for spatial information, we prefer a virtual 3-d space for the visualization.Because our image features are described in terms of veryhigh-dimensional MPEG-7 descriptors, we have to reducethem to only three dimensions for visual presentation. Thedimension reduction is realized by an appropriate weighting of the high-dimensional descriptor components corresponding to a modification of t e covariance-matrix used for Principal Component Analysis (PCA). In addition, this modification allows to overcome a problem arising from equally sized eigenvalues and provides varying eigen-spaces nearly continuously. The technique introduced is a general approach, which can be combined with other relevance feedback methods.