Real-Time visual tracking based on convolutional neural networks

doi:10.1088/1742-6596/1601/3/032053

IR > 计算机与通信学院

	Real-Time visual tracking based on convolutional neural networks
	Li, Rui1 ; Lian, Jirong 2
	2020-08-17
会议名称	2020 4th International Conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2020
会议录名称	Journal of Physics: Conference Series
卷号	1601
期号	3
会议日期	June 19, 2020 - June 21, 2020
会议地点	Jinan, Virtual, China
出版者	IOP Publishing Ltd
摘要	Traditional target tracking is based on target detection. When the target changes significantly, such as occlusion, scale change, the update of the tracking model will waste a lot of space and time resources, resulting in a very slow tracking speed, which cannot meet the actual engineering needs. In view of the above situation, an end-To-end tracking strategy is proposed, which is simpler and faster than the existing technology. The proposed tracker only needs to detect the first frame image and use it as the input of the model, and set the multi-Task loss function to predict the position of the next frame of the target and the size of the bounding box. This paper constructs a lightweight network architecture with an additional selection mechanism to avoid wasting resources for global search and matching. Through experiments, good results can be achieved on the standard data set, and tracking speeds close to one hundred frames per second are achieved, which is very competitive with existing advanced trackers. © Published under licence by IOP Publishing Ltd.
关键词	Convolutional neural networks Network architectureFrames per seconds Loss functions Selection mechanism Space and time Tracking models Tracking speed Tracking strategies Visual Tracking
DOI	10.1088/1742-6596/1601/3/032053
收录类别	EI
语种	英语
EI入藏号	20203909227990
EI主题词	Target tracking
ISSN	17426588
来源库	Compendex
引用统计	无
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/132618
专题	计算机与通信学院
作者单位	1.College of Computer and Communication, Lanzhou University of Technology, Lanzhou; 730050, China; 2.College of Computer and Communication, Lanzhou University of Technology, Lanzhou; 730050, China
第一作者单位	兰州理工大学
推荐引用方式 GB/T 7714	Li, Rui,Lian, Jirong. Real-Time visual tracking based on convolutional neural networks[C]:IOP Publishing Ltd,2020.