Searching Visual Semantic Spaces with Concept Filters

Semantic concepts cement the ability to correlate visual information to higher-level semantic concepts. Traditional image search leverages text associated with images, a low-level content-based matching, or a combination of the two. We propose a new system that uses 374 semantic concepts (derived from the LSCOM lexicon (L. Kennedy, 2006)) to semantically facilitate fast exploration of a large set of video data. This new system, when coupled with traditional image search techniques produces a very intuitive and fruitful design for targeted user interaction.