Two Ant Decision Levels and Its Application to Multi-Cell Tracking
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- 作者：Benlian Xu (19)
Qinglan Chen (20)
Mingli Lu (19)
Peiyi Zhu (19) - 关键词：Ant Colony ; Multi ; Cell Tracking ; Parameter Estimate
- 刊名：Lecture Notes in Computer Science
- 出版年：2013
- 出版时间：2013
- 年：2013
- 卷：7928
- 期：1
- 页码：297-305
- 全文大小：436KB
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Qinglan Chen (20)
Mingli Lu (19)
Peiyi Zhu (19)
19. School of Mechanical Engineering, Changshu Institute of Technology, 215500, Changshu, China
20. School of Electrical & Automatic Engineering, Changshu Institute of Technology, 215500, Changshu, China - ISSN：1611-3349
文摘
Inspired by ant’s stochastic behavior in searching of multiple food sources, a novel ant system with two ant decision levels are proposed to track multiple cells in biological field. In the ant individual level, ants within the same colony perform independently, and ant decision is determined in probability by both its intended motion model and likelihood function. In the ant cooperation level, each ant adjusts individual state within its influence region, while the global best template at current iteration is found among all ant colonies and further utilized to update ant model probability, influence region, and the probability of fulfilling task. Simulation results demonstrate that our algorithm could automatically track numerous cells and its performance is compared with the multi-Bernoulli filtering method.