@inproceedings{1e539151ce3949d08977b3b0996538dc,
title = "Activity recognition for ASD children based on joints estimation",
abstract = "Human motion recognition is a trending topic and could be applied in many areas, the motion estimation of ASD children is more challenging because of the high uncertainty of their activities, we thus introduced a novel method which is designed for estimating the upper joints and recognising their special motions, we verified the proposed method on our recorded ASD children dataset and adult dataset, the experimental results show the proposed method is effective on the dataset.",
keywords = "ASD dataset, Activity recognition, Joints estimation",
author = "Dongxu Gao and Zhaojie Ju and Yingfeng Fang and Jiangtao Cao and Chenguang Yang and Honghai Liu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 ; Conference date: 05-10-2017 Through 08-10-2017",
year = "2017",
month = nov,
day = "27",
doi = "10.1109/SMC.2017.8123076",
language = "英语",
series = "2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2951--2956",
booktitle = "2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017",
address = "美国",
}