Multimedia Information Retrieval : Promises and Challenges

The explosion of multimedia content in databases, broadcasts, streaming media, etc. has generated new requirements for more effective access to these global information repositories. Content extraction, indexing, and retrieval of multimedia data continues to be one of the most challenging and fastest-growing research areas. A consequence of the growing consumer demand for multimedia information is that sophisticated technology is needed for representing, modeling, indexing, and retrieving multimedia data. In particular, we need robust techniques to index/retrieve and compress multimedia information, new scalable browsing algorithms allowing access to very large multimedia databases, and semantic visual interfaces integrating the above components into unified multimedia browsing and retrieval systems. The aim of these systems is to handle general queries such as “find outdoor pictures or videos of an interview with James Cameron discussing the making of the Titanic film.” Answering such queries requires intelligent exploitation of both speech and visual content. For multimedia retrieval, the combination of multiple integrated media types increases the performance of content-based retrieval. Available content analysis and retrieval techniques tailored to a specific media are therefore not adequate for queries as the one mentioned above. Clearly, Multimedia Information Retrieval is a very broad area covering both structural issues (e.g. framework, storage, networking, client-server models) and intelligent content analysis and retrieval. These all need to be integrated into a seamless whole which involves expertise from a wide variety of fields.