Abstract
A trial realization of human-centered navigation for video retrieval is presented in this article. This system consists of the following functions: (a) multimodal analysis for collaborative use of multimedia data, (b) preference extraction for the system to adapt to users' individual demands, and (c) adaptive visualization for users to be guided to their desired contents. By using these functions, users can find their desired video contents more quickly and accurately than with the conventional retrieval schemes since our system can provide new pathways to the desired contents. Experimental results verify the effectiveness of the proposed system.
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