Multimedia Information Extraction Roadmap

Detecting events of interest in video where there is no accompanying sound or text; examples include surveillance video. Further advances in computer vision, perhaps combining multiple 2D views are necessary. It is interesting to note that in the UK, it is almost impossible to walk outside for 5 minutes without being captured by some surveillance video system Content extraction from noisy media, such as telephone conversations, home videos (as seen on youtube) Correlating multimedia data to other data sources, especially text sources. Frequently, multimedia data (such as video, maps, charts) are referred to in email and chat conversations. The ability to automatically and dynamically correlate these sources enhances understanding Semantic access to multimedia data, enabling granular search; perhaps this requires a comprehensive ontology of entities, relationships and events which is more geared to multimedia search. Efficient indexing and retrieval: much of multimedia content is being captured and/or delivered via mobile devices. Such devices have limited processing capabilities.