%0 Journal Article
%A LAI Yang
%A WANG Wen-dong
%A ZHANG Ji-wei
%A GAO Hui
%T Deep Learning Based Semi-Automatic Labeling System for Human Images
%D 2021
%R 10.13190/j.jbupt.2020-181
%J Journal of Beijing University of Posts and Telecommunications
%P 104-109
%V 44
%N 1
%X In view of the problem that data labeling is too dependent on hardware and manual data labeling is inefficient,a semi-automatic labeling system for human images based on deep learning is proposed. By improving the algorithm,the system increases the number of key points of the human body for feature extraction and adds motion information constraints,which improves the accuracy of video staged annotation. Experiments that employs real data sets prove the feasibility of data labeling by deep learning algorithm,and using deep learning algorithms for semi-automatic labeling is faster and more accurate.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2020-181