Quadrianto, N and Kersting, K and Tuytelaars, T and Buntine, WL (2010) Beyond 2D-grids: A dependence maximization view on image browsing. MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval. pp. 339-348.Full text not available from this repository.
Ideally, one would like to perform image search using an intuitive and friendly approach. Many existing image search engines, however, present users with sets of images arranged in some default order on the screen, typically the relevance to a query, only. While this certainly has its advantages, arguably, a more flexible and intuitive way would be to sort images into arbitrary structures such as grids, hierarchies, or spheres so that images that are visually or semantically alike are placed together. This paper focuses on designing such a navigation system for image browsers. This is a challenging task because arbitrary layout structure makes it difficult - if not impossible - to compute cross-similarities between images and structure coordinates, the main ingredient of traditional layouting approaches. For this reason, we resort to a recently developed machine learning technique: kernelized sorting. It is a general technique for matching pairs of objects from different domains without requiring cross-domain similarity measures and hence elegantly allows sorting images into arbitrary structures. Moreover, we extend it so that some images can be preselected for instance forming the tip of the hierarchy allowing to subsequently navigate through the search results in the lower levels in an intuitive way. Copyright 2010 ACM.
|Divisions:||Div F > Computational and Biological Learning|
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|Date Deposited:||15 Dec 2015 13:35|
|Last Modified:||04 May 2016 01:43|