Using a genetic algorithm for multi-hypothesis tracking

Authors:
D. B. Hillis
Affiliations:
-
Venue:
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Year:
1997

Citing 0
Cited 4

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Journal of Heuristics

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Abstract

Abstract: A technique has been devised that uses a genetic algorithm (GA) to address the multi-scan assignment problem in multitarget tracking. The problem is recast in the form of a scheduling problem, where the GA searches the space of possible orderings of detections, and a greedy heuristic is used to make the associations for a particular ordering. The resulting tracker can operate in either batch or continuous mode. In the continuous mode, a single population of hypotheses evolves on a fitness landscape that changes with each new scan of data.