Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction

Ruijing Yang, Ziyu Guan, Zitong Yu, Xiaoyi Feng, Jinye Peng, Guoying Zhao

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Automatic pain recognition is paramount for medical diagnosis and treatment. The existing works fall into three categories: assessing facial appearance changes, exploiting physiological cues, or fusing them in a multi-modal manner. However, (1) appearance changes are easily affected by subjective factors which impedes objective pain recognition. Besides, the appearance-based approaches ignore long-range spatial-temporal dependencies that are important for modeling expressions over time; (2) the physiological cues are obtained by attaching sensors on human body, which is inconvenient and uncomfortable. In this paper, we present a novel multi-task learning framework which encodes both appearance changes and physiological cues in a non-contact manner for pain recognition. The framework is able to capture both local and long-range dependencies via the proposed attention mechanism for the learned appearance representations, which are further enriched by temporally attended physiological cues (remote photoplethysmography, rPPG) that are recovered from videos in the auxiliary task. This framework is dubbed rPPG-enriched Spatio-Temporal Attention Network (rSTAN) and allows us to establish the state-of-the-art performance of non-contact pain recognition on publicly available pain databases. It demonstrates that rPPG predictions can be used as an auxiliary task to facilitate non-contact automatic pain recognition.

源语言英语
主期刊名Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
编辑Zhi-Hua Zhou
出版商International Joint Conferences on Artificial Intelligence
1231-1237
页数7
ISBN(电子版)9780999241196
DOI
出版状态已出版 - 2021
活动30th International Joint Conference on Artificial Intelligence, IJCAI 2021 - Virtual, Online, 加拿大
期限: 19 8月 202127 8月 2021

出版系列

姓名IJCAI International Joint Conference on Artificial Intelligence
ISSN(印刷版)1045-0823

会议

会议30th International Joint Conference on Artificial Intelligence, IJCAI 2021
国家/地区加拿大
Virtual, Online
时期19/08/2127/08/21

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