TRECVID 2010 Known-item Search (KIS) Task by I2R

The KIS task can be regarded as an extreme case of target-specific video search, in which the query aims to uniquely locate a single true answer. Locating the unique video for a query, however, poses new challenges over existing information retrieval approaches. Our participation in TRECVID this year focuses on how to adapt traditional information retrieval, specifically video search, methods to KIS in both automatic and interactive setting. In automatic KIS, as there exists a single true answer for each query, the input queries are expected to present distinctive information locating a unique entity but not a broad topic covering a number of relevant videos. Therefore, query formulation is one of our focuses in automatic KIS. On the other end of the spectrum, our emphasis in interactive KIS is two-fold. First, an intuitive and user-friendly user interface is developed to facilitate the browsing of returned videos. As the query is usually specific, we postulate that searchers can quickly reject most of the negative videos after seeing a few keyframes of the video. This premise of “fast rejection” motivates us to leverage the storyboard to pre-visualize a video. When users can not reject a returned video as negative, he/she may indicate it as a relevant one. By collecting a number of relevant videos, the searchers can perform relevance feedback to refine the retrieval and continue the search. The automatic and interactive KIS achieve MAP of 0.454 and 0.727 respectively, showing the effectiveness of the proposed methods.