Using a genetic algorithm for multi-hypothesis tracking

被引：11
|
作者：
Hillis, DB
机构：
来源：
NINTH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 1997年
关键词：
D O I：
10.1109/TAI.1997.632244
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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. We 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.
引用
收藏
页码：112 / 117
页数：6
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