Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight

doi:10.3390/s18041292

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	Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight
	Guo, S. Q.; Zhang, T.; Song, Y. L.; Qian, F.
	2018
发表期刊	Sensors
ISSN	1424-8220
卷号	18 期号:4 页码:17
摘要	This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.
关键词	object tracking particle swarm optimization particle maturity inertia weight color feature Chemistry Electrochemistry Instruments & Instrumentation
DOI	10.3390/s18041292
收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/60929
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Guo, S. Q.,Zhang, T.,Song, Y. L.,et al. Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight[J]. Sensors,2018,18(4):17.
APA	Guo, S. Q.,Zhang, T.,Song, Y. L.,&Qian, F..(2018).Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.Sensors,18(4),17.
MLA	Guo, S. Q.,et al."Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight".Sensors 18.4(2018):17.

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