NDLI: Novel visual tracking approach via ant lion optimiser

Content Provider	IET Digital Library
Author	Zhang, Huanlong Gao, Zeng Zhang, Jie Lu, Xiankai Chen, Jian Nie, Guohao Qian, Xiaoliang
Abstract	Ant lion optimiser (ALO) is a new nature-inspired swarm intelligence optimisation algorithm that mimics the hunting mechanism of antlions in nature. ALO has been proved to have the merits of high exploitation and convergence speed benefiting from adaptive boundary shrinking mechanism and elitism. In this work, visual tracking is expressed as searching for object in whole search space by interaction between antlions and ants. A novel ALO-based visual tracking framework is proposed and the adaptation and sensitivity of the parameters in ALO are discussed to improve tracking performance. In addition, considering that ALO tracker needs a lot of iteration consumption, kernel correlation filter with deep feature is integrated into the ALO tracking framework (ALOKCF) to improve track efficiency. Extensive experimental results prove that the ALO tracker is very competitive compared to other trackers, especially for abrupt motion tracking. At the same time, two visual tracking benchmarks are used to verify ALOKCF tracker achieves state-of-the-art performance.
Starting Page	727
Ending Page	735
Page Count	9
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 4, Mar (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5702
Journal	IET Image Processing
Publisher Date	2019-11-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Abrupt Motion Tracking Adaptive Boundary Shrinking Elitism Adaptive Boundary Shrinking Mechanism ALO-based Visual Tracking Framework Ant Lion Optimiser Computer Vision And Image Processing Technique Convergence Convergence Speed Filtering Method in Signal Processing Filtering Theory High Exploitation Nature-inspired Swarm Intelligence Optimisation Algorithm Object Tracking Optical, Image And Video Signal Processing Optimisation Technique Particle Swarm Optimisation Search Problem Search Space Sensitivity Analysis Track Efficiency Tracking Performance Visual Tracking Benchmarks
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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