Using Multiple Segmentations to Discover Objects and their Extent in Image Collections

@article{Russell2006UsingMS,
  title={Using Multiple Segmentations to Discover Objects and their Extent in Image Collections},
  author={Bryan C. Russell and William T. Freeman and Alexei A. Efros and Josef Sivic and Andrew Zisserman},
  journal={2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)},
  year={2006},
  volume={2},
  pages={1605-1614}
}
Given a large dataset of images, we seek to automatically determine the visually similar object and scene classes together with their image segmentation. To achieve this we combine two ideas: (i) that a set of segmented objects can be partitioned into visual object classes using topic discovery models from statistical text analysis; and (ii) that visual object classes can be used to assess the accuracy of a segmentation. To tie these ideas together we compute multiple segmentations of each… CONTINUE READING
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