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      Pattern discovery for object categorization

      Zhang, Edmond Yiwen; Mayo, Michael
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      objectclass.pdf
      1.996Mb
      DOI
       10.1109/IVCNZ.2008.4762071
      Link
       ieeexplore.ieee.org
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      Citation
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      Zhang, E. & Mayo, M. (2008). Pattern discovery for object categorization. In Proceeding of 23rd International Conference Image and Vision Computing New Zealand 2008(IVCNZ 2008).
      Permanent Research Commons link: https://hdl.handle.net/10289/2173
      Abstract
      This paper presents a new approach for the object categorization problem. Our model is based on the successful `bag of words' approach. However, unlike the original model, image features (keypoints) are not seen as independent and orderless. Instead, our model attempts to discover intermediate representations for each object class. This approach works by partitioning the image into smaller regions then computing the spatial relationships between all of the informative image keypoints in the region. The results show that the inclusion of spatial relationships leads to a measurable increase in performance for two of the most challenging datasets.
      Date
      2008
      Type
      Conference Contribution
      Publisher
      IEEE Press
      Rights
      This article has been published in the Proceeding of 23rd International Conference Image and Vision Computing New Zealand 2008 (IVCNZ 2008). ©2008 IEEE.
      Collections
      • Computing and Mathematical Sciences Papers [1441]
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