Information fusion for image analysis: Geospatial foundations for higher-level fusion

Author(s): McKenna, T.S. | Rhodes, B.J. | Waxman, A.M. |

Year: 2002

Citation: Proceedings of the 5th International Conference on Information Fusion, Annapolis, July.

Abstract: In support of the AFOSR program in Information Fusion, the CNS Technology Laboratory at Boston University is developing and applying neural models of image and signal processing, pattern learning and recognition, associative learning dynamics, and 3D visualization, to the domain of Information Fusion for Image Analysis in a geospatial context. Our research is focused by a challenge problem involving the emergence of a crisis in an urban environment, brought on by a terrorist attack or other man-made or natural disaster. We aim to develop methods aiding preparation and monitoring of the battlespace, deriving context from multiple sources of imagery (high-resolution visible and low-resolution hyperspectral) and signals (GMTI from moving vehicles, and ELINT from emitters). This context will serve as a foundation, in conjunction with existing knowledge nets, for exploring neural methods in higherlevel information fusion supporting situation assessment and creation of a common operating picture (COP).

Topics: Image Analysis, Applications: Information Fusion, Other, Models: Other,

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