AutoHR: A Strong End-to-End Baseline for Remote Heart Rate Measurement With Neural Searching

doi:10.1109/LSP.2020.3007086

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	AutoHR: A Strong End-to-End Baseline for Remote Heart Rate Measurement With Neural Searching
	Yu, Zitong 1; Li, Xiaobai 1; Niu, Xuesong 2,3; Shi, Jingang 4,5; Zhao, Guoying 6
刊名	IEEE SIGNAL PROCESSING LETTERS
	2020
卷号	27 页码:1245-1249
关键词	RPPG heart rate neural architecture search
ISSN号	1070-9908
DOI	10.1109/LSP.2020.3007086
英文摘要	Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e.g., remote healthcare). Existing end-to-end rPPG and heart rate (HR) measurement methods from facial videos are vulnerable to the less-constrained scenarios (e.g., with head movement and bad illumination). In this letter, we explore the reason why existing end-to-end networks perform poorly in challenging conditions and establish a strong end-to-end baseline (AutoHR) for remote HR measurement with neural architecture search (NAS). The proposed method includes three parts: 1) a powerful searched backbone with novel Temporal Difference Convolution (TDC), intending to capture intrinsic rPPG-aware clues between frames; 2) a hybrid loss function considering constraints from both time and frequency domains; and 3) spatio-temporal data augmentation strategies for better representation learning. Comprehensive experiments are performed on three benchmark datasets, and we achieved superior performance on both intra- and cross-dataset testings.
资助项目	National Natural Science Foundation of China[61772419] ; Academy of Finland[316765] ; ICT 2023 project[328115] ; Infotech Oulu
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000554896000003
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/15861]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhao, Guoying
作者单位	1.Univ Oulu, Ctr Machine Vis & Signal Anal CMVS, Oulu 90014, Finland 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Xi An Jiao Tong Univ, Sch Software Engn, Xian 710049, Shaanxi, Peoples R China 5.Univ Oulu, CMVS, Oulu 90014, Finland 6.Northwest Univ, Sch Informat & Technol, Xian 710069, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Yu, Zitong,Li, Xiaobai,Niu, Xuesong,et al. AutoHR: A Strong End-to-End Baseline for Remote Heart Rate Measurement With Neural Searching[J]. IEEE SIGNAL PROCESSING LETTERS,2020,27:1245-1249.
APA	Yu, Zitong,Li, Xiaobai,Niu, Xuesong,Shi, Jingang,&Zhao, Guoying.(2020).AutoHR: A Strong End-to-End Baseline for Remote Heart Rate Measurement With Neural Searching.IEEE SIGNAL PROCESSING LETTERS,27,1245-1249.
MLA	Yu, Zitong,et al."AutoHR: A Strong End-to-End Baseline for Remote Heart Rate Measurement With Neural Searching".IEEE SIGNAL PROCESSING LETTERS 27(2020):1245-1249.