Utilization of Riemann surfaces in sensor data fusion

Michael Patrick Cain

doi:10.1117/12.256324

30 October 1996 Utilization of Riemann surfaces in sensor data fusion

Michael Patrick Cain

Proceedings Volume 2905, Sensor Fusion and Distributed Robotic Agents; (1996) https://doi.org/10.1117/12.256324
Event: Photonics East '96, 1996, Boston, MA, United States

Abstract

The use of Riemann surfaces offers an alternative approach to the characterization of object classes. In a situation where data from multiple sensors is available, the sensor observables can be used as the coordinates which define the space occupied by the class surfaces. The curvature of the surfaces will be governed by the underlying correlations between the phenomenologies of interest and the viewing conditions. The result is a natural coordinate system in which to implement classification algorithms. In this paper, a simple two-dimensional example is presented which introduces the underlying mathematics of the approach. A traditional statistical classifier is then used to examine classification performance. Extending the approach to include non-collocated sensors, sensor measurement error, and noise sources is also briefly discussed.

Citation Download Citation

Michael Patrick Cain "Utilization of Riemann surfaces in sensor data fusion", Proc. SPIE 2905, Sensor Fusion and Distributed Robotic Agents, (30 October 1996); https://doi.org/10.1117/12.256324

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