Visualization, Estimation and User-Modeling for Interactive
Browsing of Image Libraries
We present a user-centric system for visualization and layout for content-based image retrieval
and browsing. Image features (visual and/or semantic) are analyzed to display and group retrievals as thumbnails in a
2-D spatial layout which conveys mutual similarities. Moreover, a novel subspace feature weighting technique is
proposed and used to modify 2-D layouts in a variety of context-dependent ways. An efficient computational technique
for subspace weighting and re-estimation leads to a simple user-modeling framework whereby the system can learn to
display query results based on layout examples (or relevance feedback) provided by the user. The resulting retrieval,
browsing and visualization engine can adapt to the user's (time-varying) notions of con-tent, context and preferences
in style of interactive navigation. Monte Carlo simulations with synthetic "user-layouts" as well as pilot user
studies have demonstrated the ability of this framework to accurately model or "mimic" users by automatically
generating layouts according to their preferences.
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