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A bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds

文献类型：期刊论文

作者Huang, Xiao1; Qiao, Hong2; Li, Hui1; Jiang, Zhihong1
刊名IMAGE AND VISION COMPUTING
出版日期2021-10-01
卷号114页码:13
ISSN号0262-8856
关键词Bioinspiration Small-target motion detector Robotic visual perception Spatiotemporal energy model
DOI10.1016/j.imavis.2021.104266
通讯作者Li, Hui(lihui2011@bit.edu.cn) ; Jiang, Zhihong(jiangzhihong@bit.edu.cn)
英文摘要Robust and accurate detection of small moving targets in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform search and tracking tasks. Inspired by the neural circuitry of elementary motion vision in the mammalian retina, this paper proposes a bioinspired retinal neural network based on a new neurodynamics-based temporal filtering and multiform 2-D spatial Gabor filtering. This model can estimate motion direction accurately via only two perpendicular spatiotemporal filtering signals, and respond to small targets of different sizes and velocities through adjusting the dendrite field size of spatial filter. Meanwhile, an algorithm of directionally selective inhibition is proposed to suppress the target-like features in the moving background, which can reduce the influence of background motion effectively. Extensive synthetic and real-data experiments show that the proposed model works stably for small targets of a wider size and velocity range, and has better detection performance than other bioinspired models. Additionally, it can also extract the information of motion direction and motion energy accurately and rapidly. (c) 2021 Elsevier B.V. All rights reserved.
WOS关键词BIPOLAR CELLS ; OBJECT DETECTION ; GANGLION-CELLS ; PERCEPTION ; NAVIGATION ; DIRECTION ; NEURONS
资助项目National Key Research and Development Program of China[2018YFB1305300] ; China Postdoctoral Science Foundation[2020TQ0039] ; National Natural Science Foundation of China[61733001] ; National Natural Science Foundation of China[U2013602] ; National Natural Science Foundation of China[61873039] ; National Natural Science Foundation of China[U1913211] ; National Natural Science Foundation of China[U1713215]
WOS研究方向Computer Science ; Engineering ; Optics
语种英语
出版者ELSEVIER
WOS记录号WOS:000697051200010
资助机构National Key Research and Development Program of China ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/45765]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者Li, Hui; Jiang, Zhihong
作者单位1.Beijing Inst Technol, Adv Innovat Ctr Intelligent Robots & Syst, Key Lab Biomimet Robots & Syst, Chinese Minist Educ,Sch Mechatron Engn, Beijing 100081, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Huang, Xiao,Qiao, Hong,Li, Hui,et al. A bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds[J]. IMAGE AND VISION COMPUTING,2021,114:13.
APA Huang, Xiao,Qiao, Hong,Li, Hui,&Jiang, Zhihong.(2021).A bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds.IMAGE AND VISION COMPUTING,114,13.
MLA Huang, Xiao,et al."A bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds".IMAGE AND VISION COMPUTING 114(2021):13.

入库方式： OAI收割

来源：自动化研究所

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