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3D Human Pose Estimation Using Ultra-low Resolution Thermal Images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Can we estimate 3D human pose from ultra-low resolution thermal images (e.g., 8 × 8 pixels)? This study explores this possibility. Thermal images capture radiation intensity, minimizing personal information exposure, and are commonly used in devices like air conditioners. We propose a framework that uses 8 × 8 thermal images for 3D human pose estimation, enhancing privacy and efficiency. To overcome challenges from subject and ambient temperature variations, we employ adversarial learning with discriminators for subject and temperature, ensuring robust and invariant feature extraction.

Original languageEnglish
Title of host publicationProceedings - SIGGRAPH Asia 2024 Posters, SA 2024
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9798400711381
DOIs
Publication statusPublished - 2024 Dec 3
Event2024 SIGGRAPH Asia 2024 Posters, SA 2024 - Tokyo, Japan
Duration: 2024 Dec 32024 Dec 6

Publication series

NameProceedings - SIGGRAPH Asia 2024 Posters, SA 2024

Conference

Conference2024 SIGGRAPH Asia 2024 Posters, SA 2024
Country/TerritoryJapan
CityTokyo
Period24/12/324/12/6

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

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