iMap: a stable layout for navigating large image collections with embedded search

Chaoli Wang; John P. Reese; Huan Zhang; Jun Tao; Robert J. Nemiroff

doi:10.1117/12.999313

4 February 2013 iMap: a stable layout for navigating large image collections with embedded search

Chaoli Wang, John P. Reese, Huan Zhang, Jun Tao, Robert J. Nemiroff

Proceedings Volume 8654, Visualization and Data Analysis 2013; 86540K (2013) https://doi.org/10.1117/12.999313
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

Effective techniques for organizing and visualizing large image collections are in growing demand as visual search gets increasingly popular. Targeting an online astronomy archive with thousands of images, we present our solution for image search and clustering based on the evaluation image similarity using both visual and textual information. To lay out images, we introduce iMap, a treemap-based representation for visualizing and navigating image search and clustering results. iMap not only makes effective use of available display area to arrange images but also maintains stable update when images are inserted or removed during the query. We also develop an embedded visualization that integrates image tags for in-place search refinement. We show the effectiveness of our approach by demonstrating experimental results and conducting a comparative user study.

Citation Download Citation

Chaoli Wang, John P. Reese, Huan Zhang, Jun Tao, and Robert J. Nemiroff "iMap: a stable layout for navigating large image collections with embedded search", Proc. SPIE 8654, Visualization and Data Analysis 2013, 86540K (4 February 2013); https://doi.org/10.1117/12.999313

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