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Proceedings Paper

A hybrid approach to the fusion of partially coinciding alarms from asynchronous or specialized detectors
Author(s): Brandon Smock; Joseph Wilson; Taylor Glenn
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Paper Abstract

The accurate detection of a diverse set of targets often requires the use of multiple sensor modalities and algorithms. Fusion approaches can be used to combine information from multiple sensors or detectors. But typical fusion approaches are not suitable when detectors do not operate on all of the same locations of interest, or when detectors are specialized to detect disjoint sets of target types. Run Packing is an algorithm we developed previously to optimally combine detectors when their output never coincides, which can be expected when the detectors are specialized to detect different target types. But when asynchronous detectors sometimes coincide, or specialized detectors sometimes detect the same target, Run Packing ignores this coincidence information and thus may be suboptimal in certain cases. In this paper, we show how multi-detector fusion involving partially­ coinciding alarms can be re-framed as an equivalent fusion problem that is optimally addressed by Run Packing. This amounts to a hierarchical or hybrid approach involving fusion methods to join coinciding alarms at the same location into a single unified alarm and then using Run Packing to optimally fuse the resulting set of non­ coinciding alarms. We report preliminary results of applying the method in a few typical landmine detection scenarios to demonstrate its potential utility.

Paper Details

Date Published: 20 June 2014
PDF: 7 pages
Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 90911D (20 June 2014); doi: 10.1117/12.2054220
Show Author Affiliations
Brandon Smock, Univ. of Florida (United States)
Joseph Wilson, Univ. of Florida (United States)
Taylor Glenn, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 9091:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII
Ivan Kadar, Editor(s)

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