MonkeyTrail: A scalable video-based method for tracking macaque movement trajectory in daily living cages

doi:10.24272/j.issn.2095-8137.2021.353

	MonkeyTrail: A scalable video-based method for tracking macaque movement trajectory in daily living cages
	Liu, Meng-Shi 7,8,9; Gao, Jin-Quan 5,6; Hu, Gu-Yue 1,7,8,9; Hao, Guang-Fu 7,8,9; Jiang, Tian-Zi 4,7,8,9; Zhang, Chen 2,3; Yu, Shan 7,8,9
刊名	ZOOLOGICAL RESEARCH
	2022-05-18
卷号	43 期号:3 页码:343-351
关键词	Movement trajectory tracking Video-based behavioral analyses Background subtraction Virtual empty background Occlusion
ISSN号	2095-8137
DOI	10.24272/j.issn.2095-8137.2021.353
通讯作者	Zhang, Chen(czhang@ccmu.edu.cn) ; Yu, Shan(shan.yu@nlpr.ia.ac.cn)
英文摘要	Behavioral analysis of macaques provides important experimental evidence in the field of neuroscience. In recent years, video-based automatic animal behavior analysis has received widespread attention. However, methods capable of extracting and analyzing daily movement trajectories of macaques in their daily living cages remain underdeveloped, with previous approaches usually requiring specific environments to reduce interference from occlusion or environmental change. Here, we introduce a novel method, called MonkeyTrail, which satisfies the above requirements by frequently generating virtual empty backgrounds and using background subtraction to accurately obtain the foreground of moving animals. The empty background is generated by combining the frame difference method (FDM) and deep learning-based model (YOLOv5). The entire setup can be operated with low-cost hardware and can be applied to the daily living environments of individually caged macaques. To test MonkeyTrail performance, we labeled a dataset containing >8 000 video frames with the bounding boxes of macaques under various conditions as ground-truth. Results showed that the tracking accuracy and stability of MonkeyTrail exceeded that of two deep learning-based methods (YOLOv5 and Single-Shot MultiBox Detector), traditional frame difference method, and naive background subtraction method. Using MonkeyTrail to analyze long-term surveillance video recordings, we successfully assessed changes in animal behavior in terms of movement amount and spatial preference. Thus, these findings demonstrate that MonkeyTrail enables low-cost, large-scale daily behavioral analysis of macaques.
资助项目	National Key Research and Development Program of China[2017YFA0105203] ; National Key Research and Development Program of China[2017YFA0105201] ; National Science Foundation of China[31771076] ; National Science Foundation of China[81925011] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB32040201] ; Key-Area Research and Development Program of Guangdong Province[2019B030335001] ; Beijing Academy of Artificial Intelligence
WOS关键词	MOTOR DEFICITS ; SYSTEM ; MODEL ; MOTION
WOS研究方向	Zoology
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000798008000004
资助机构	National Key Research and Development Program of China ; National Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) ; Key-Area Research and Development Program of Guangdong Province ; Beijing Academy of Artificial Intelligence
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/49464]
专题	自动化研究所_脑网络组研究中心
通讯作者	Zhang, Chen; Yu, Shan
作者单位	1.Natl Univ Singapore, Sch Comp, Singapore 119077, Singapore 2.Capital Med Univ, Adv Innovat Ctr Human Brain Protect, Beijing 100069, Peoples R China 3.Capital Med Univ, Dept Neurobiol, Sch Basic Med Sci, Beijing Key Lab Neural Regenerat & Repair, Beijing 100069, Peoples R China 4.Univ Elect Sci & Technol China, Sch Life Sci & Technol, Minist Educ, Key Lab NeuroInformat, Chengdu 611731, Sichuan, Peoples R China 5.Beijing Life Biosci Co Ltd, Model R&D Ctr, Beijing 100176, Peoples R China 6.SAFE Pharmaceut Technol Co Ltd, Technol Management Ctr, Beijing 100176, Peoples R China 7.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China 8.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 9.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Meng-Shi,Gao, Jin-Quan,Hu, Gu-Yue,et al. MonkeyTrail: A scalable video-based method for tracking macaque movement trajectory in daily living cages[J]. ZOOLOGICAL RESEARCH,2022,43(3):343-351.
APA	Liu, Meng-Shi.,Gao, Jin-Quan.,Hu, Gu-Yue.,Hao, Guang-Fu.,Jiang, Tian-Zi.,...&Yu, Shan.(2022).MonkeyTrail: A scalable video-based method for tracking macaque movement trajectory in daily living cages.ZOOLOGICAL RESEARCH,43(3),343-351.
MLA	Liu, Meng-Shi,et al."MonkeyTrail: A scalable video-based method for tracking macaque movement trajectory in daily living cages".ZOOLOGICAL RESEARCH 43.3(2022):343-351.