MLF 2013 - Special Session on Multi-Level Fusion: Bridging the Gap Between High and Low Level Fusion

The exploitation of all relevant information originating from a growing mass of heterogeneous sources, both device-based (sensors, video, etc.) and human-generated (text, voice, etc.), is a key factor for the production of timely, comprehensive and most accurate description of a situation or phenomenon. There is a growing need to effectively identify relevant information from the mass available, and exploit it through automatic fusion for timely, comprehensive and accurate situation awareness. The processing of sensor-produced data is now a proven, mature technology and great advances have been made in analysis of text-based information based upon computational linguistics. However, up until now researchers in these two communities have operated within their respective communities with little cross-pollination of ideas, experience and methodologies. As a result, timely, comprehensive and precise situation awareness is impossible because of this communication gap. This is caused by the lack of an integrative approach to processing sensor data (low-level fusion) and semantically rich information (high-level fusion) in a holistic manner. The proposed special session will bring together researchers from both fusion communities, fostering the discussion on the commonalities and differences in their research methodologies, and proposing viable multi-level fusion solutions to address challenging problems or relevant applications.