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

doi:10.1016/j.imavis.2021.104266

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	A bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds
	Huang, Xiao1 ; Qiao, Hong2 ; Li, Hui 1; Jiang, Zhihong 1
发表期刊	IMAGE AND VISION COMPUTING
ISSN	0262-8856
	2021-10-01
卷号	114 页码:13
通讯作者	Li, Hui(lihui2011@bit.edu.cn) ; Jiang, Zhihong(jiangzhihong@bit.edu.cn)
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.
关键词	Bioinspiration Small-target motion detector Robotic visual perception Spatiotemporal energy model
DOI	10.1016/j.imavis.2021.104266
关键词[WOS]	BIPOLAR CELLS ; OBJECT DETECTION ; GANGLION-CELLS ; PERCEPTION ; NAVIGATION ; DIRECTION ; NEURONS
收录类别	SCI
语种	英语
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]
项目资助者	National Key Research and Development Program of China ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China
WOS研究方向	Computer Science ; Engineering ; Optics
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Optics
WOS记录号	WOS:000697051200010
出版者	ELSEVIER
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/45766
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
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.