@inproceedings{458343d0e6154e71b61434fcb3707f9d,
title = "Pixels2Pose: Super-Resolution Time-of-Flight Imaging for 3D Pose Estimation",
abstract = "The process of tracking human anatomy in computer vision is called pose estimation. It traditionally requires advanced equipment. We develop a system that estimates the 3D poses of people from a cost-effective and compact time-of-flight sensor.",
keywords = "cs.CV",
author = "Alice Ruget and Max Tyler and Germ{\'a}n Mora-Mart{\'i}n and Stirling Scholes and Feng Zhu and Istvan Gyongy and Brent Hearn and Steve McLaughlin and Abderrahim Halimi and Jonathan Leach",
note = "Funding Information: This work was supported by EPSRC through grants EP/S001638/1, EP/T00097X/1 and EP/S026428/1. Also it is supported by the UK Royal Academy of Engineering Research Fellowship Scheme (Project RF/201718/17128) and DSTL Dasa project DSTLX1000147844. We thank the authors of OpenPose [1] for their code. Code for generating the 3D pose from the ToF sensor can be found at https://github.com/HWQuantum/Real-time-low-cost-multi-person-3D-pose-estimation. The trained networks are available at https://researchportal.hw.ac.uk/en/datasets/real-time-low-cost-multi-person-3d-pose-estimation. Publisher Copyright: {\textcopyright} 2022 The Author(s); Imaging Systems and Applications 2022, ISA 2022 ; Conference date: 11-07-2022 Through 15-07-2022",
year = "2022",
doi = "10.1364/ISA.2022.ITh5D.5",
language = "English",
booktitle = "Imaging Systems and Applications 2022",
publisher = "OPTICA Publishing Group",
}