Multi-Level Unsupervised Domain Adaption for Privacy-protected In-bed Pose Estimation

Ziheng Chi, Shaozhi Wang, Xinyue Li, Chun Tzu Chang, Md Islam, Akshay Holkar, Samantha Pronger, Tianshan Liu, Kin Man Lam, Xiangjian He

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In-bed pose estimation is of great value in current health-monitoring systems. In this paper, we solve a cross-domain pose estimation problem, in which a fully annotated uncovered training set is used for pose estimation learning, and a large-scale unlabelled data set of covered images is employed for unsupervised domain adaptation. To tackle this challenging problem, we propose a multi-level domain adaptation framework, which learns a generalizable pose estimation network based three levels of adaptation. We evaluate the proposed framework on a public in-bed pose estimation benchmark. The results demonstrate that our proposed framework can effectively generalize the learned knowledge from the uncovered source domain to the covered target domain for privacy-protected in-bed pose estimation.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Imaging Technology, IWAIT 2022
EditorsMasayuki Nakajima, Shogo Muramatsu, Jae-Gon Kim, Jing-Ming Guo, Qian Kemao
PublisherSPIE
Volume12177
ISBN (Electronic)9781510653313
DOIs
Publication statusPublished - Apr 2022
Event2022 International Workshop on Advanced Imaging Technology, IWAIT 2022 - Hong Kong, China
Duration: 4 Jan 20226 Jan 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12177
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2022 International Workshop on Advanced Imaging Technology, IWAIT 2022
Country/TerritoryChina
CityHong Kong
Period4/01/226/01/22

Keywords

  • In-bed human pose estimation
  • Privacy protection
  • Unsupervised domain adaption

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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