Interactive content-based retrieval of video

Abstract

In this paper, we describe a system for content-based retrieval of video that involves a series of query interactions with the user. The proposed approach allows the user to iteratively and selectively integrate different feature- and model-based methods of querying in the search process. This allows the user to choose among different retrieved content, features and matching dimensions, and classifiers, as appropriate, given the query objective and interim retrieval results. We investigate several approaches for integrating feature- and model-based queries and results in successive query rounds including iterative filtering, score aggregation, and relevance feedback searching. We describe experimental results of applying the interactive content-based retrieval method to an automatically indexed corpus of 11 hours of video.