B. Moghaddam1,2, Qi Tian1,2, N. Lesh1,2, Chia Shen1,2, T.S. Huang1,2
1Beckman Institute, University of Illinois, Urbana-Champaign, IL, USA
2Mitsubishi Electric Research Laboratory, Cambridge, MA, USA
Tóm tắt
We present visualization and layout algorithms that can enhance informal story-telling using personal digital data such as photos in a face-to-face social setting. In order to build a more intuitive browser for retrieval, navigation and story-telling, we introduce a novel optimized layout technique for large image sets, which respects (context-sensitive) mutual similarities as visualized on a shared 2-D display (a table-top). The experimental results show a more perceptually intuitive and informative visualization of traditional CBIR-based retrievals, providing not only a better understanding of the query context but also aiding the user informing new queries. A framework for user-modeling is also introduced and tested. This allows the system to adapt to the user's preference and integrate relevance feedback.