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A Measure of Perceptual Aliasing in Image Descriptors

  • Author / Creator
    Wang, Jiemin
  • This thesis is concerned with a measure of perceptual aliasing in image descriptors. Perceptual aliasing occurs when the one-to-one mapping relations between world states (objects) and their representation (descriptors) are not maintained. Our method measures the discriminating power of an image descriptor in terms of its ability to distinguish between images of different objects and to match images of the same object. Specifically, our method runs spectral clustering on the similarity matrix computed with descriptors of known image clusters and measures the performance of an image descriptor by its ability to maintain the original clusters, using two indices, MRI-1 and MRI-2, that are based on the Rand index. Experiments on MRI versus precision and recall show that our proposed metrics are more appropriate for applications such as content-based image retrieval in which image clustering is a critical step.

  • Subjects / Keywords
  • Graduation date
    2013-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3M98K
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Zhang, Hong (Computing Science)
  • Examining committee members and their departments
    • Szepesvári, Csaba (Computing Science)
    • Ray, Nilanjan (Computing Science)