Brewer, Nathan; Liu, Nianjun; Wang, Lei
Image partitioning separates an image into multiple visually and semantically homogeneous regions, providing a summary of visual content. Knowing that human observers focus on interesting objects or regions when interpreting a scene, and envisioning the usefulness of this focus in many computer vision tasks, this paper develops a user-attention adaptive image partitioning approach. Given a set of pairs of oversegments labeled by a user as "should be merged" or "should not be merged", the...[Show more]
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