Recent Advances and Open Issues of Digital Image/Video Search
With the prevalent success of Internet search, researchers are facing new opportunities and challenges— developing next-generation multimedia search technologies that may reach a performance level similar to that of text search. Despite the grand scale of the challenges, some promising grounds have been revealed recently. In this talk, I will focus on two exciting areas—semantic annotation and multimedia document ranking. For the former, we are witnessing the significant developments in large-scale image/video collection for benchmarking, multimedia lexicons, and a large number of semantic classifiers. For example, we have developed classifiers for 374 semantic concepts with encouraging performance using more than 160 hours of digital videos in TRECVID 2006. The collective power of a large number of semantic models offers great potential—I will share recent results of this approach in video searching, topic threading, and temporal pattern mining. For the second area, I will present recent efforts to model video retrieval as a document ranking problem similar to that used for page ranking of web search. I will discuss how the semantic models and visual duplicate information may be used to approximate the information required in constructing document link graphs. I will conclude the talk with discussions of open issues in this dynamic and exciting area.