Activity recognition for ASD children based on joints estimation

Dongxu Gao; Zhaojie Ju; Yinfeng Fang; Jiangtao Cao; Chenguang Yang; Honghai Liu

doi:10.1109/SMC.2017.8123076

Activity recognition for ASD children based on joints estimation

Dongxu Gao, Zhaojie Ju, Yinfeng Fang, Jiangtao Cao, Chenguang Yang, Honghai Liu

Liaoning University of Petroleum and Chemical Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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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.

Original language	English
Title of host publication	2017 IEEE International Conference on Systems, Man, and Cybernetics
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	6
ISBN (Electronic)	978-1538616451
ISBN (Print)	978-1538616468
DOIs	https://doi.org/10.1109/SMC.2017.8123076
Publication status	Published - 1 Dec 2017

Keywords

joints estimation
activity recognition
ASD dataset

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10.1109/SMC.2017.8123076

SMC2017
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Accepted author manuscript (Post-print), 855 KB

Cite this

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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.",

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AU - Gao, Dongxu

AU - Ju, Zhaojie

AU - Fang, Yinfeng

AU - Cao, Jiangtao

AU - Yang, Chenguang

AU - Liu, Honghai

PY - 2017/12/1

Y1 - 2017/12/1

N2 - 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.

AB - 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.

KW - joints estimation

KW - activity recognition

KW - ASD dataset

U2 - 10.1109/SMC.2017.8123076

DO - 10.1109/SMC.2017.8123076

M3 - Conference contribution

SN - 978-1538616468

BT - 2017 IEEE International Conference on Systems, Man, and Cybernetics

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Activity recognition for ASD children based on joints estimation

Abstract

Keywords

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