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Shape Matching by Segmentation Averaging

  • Hongzhi Wang
  • John Oliensis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5302)

Abstract

We use segmentations to match images by shape. To address the unreliability of segmentations, we give a closed form approximation to an average over all segmentations. Our technique has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the “central” segmentation minimizing the average distance to all segmentations of an image. Our methods for segmentation and object detection perform competitively, and we also show promising results in tracking and edge–preserving smoothing.

Keywords

Image Segmentation Segmentation Algorithm Object Detection Spatial Pyramid Spatial Pyramid Match 
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

  • Hongzhi Wang
    • 1
  • John Oliensis
    • 1
  1. 1.Stevens Institute of TechnologyUSA

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