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Publication Authors

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Dr. Gerd Reis

Eric Thil

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Sk Aziz Ali

Rashed Al Koutayni
Yuriy Anisimov

Jilliam Maria Diaz Barros

Ramy Battrawy
Hammad Butt

Mahdi Chamseddine
Steve Dias da Cruz

Fangwen Shu

Torben Fetzer

Michael Fürst

Christiano Couto Gava

Tewodros Amberbir Habtegebrial
Khurram Hashmi

Jigyasa Singh Katrolia

Andreas Kölsch
Onorina Kovalenko

Stephan Krauß
Paul Lesur

Muhammad Jameel Nawaz Malik
Michael Lorenz

Mina Ameli

Nareg Minaskan Karabid

Pramod Murthy

Mathias Musahl

Peter Neigel

Manthan Pancholi
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar

Alexander Schäfer

René Schuster

Mohamed Selim

Dennis Stumpf

Yongzhi Su

Xiaoying Tan
Yaxu Xie
Murad Almadani

Ahmet Firintepe

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão
HMDPose: A large-scale trinocular IR Augmented Reality Glasses Pose Dataset
HMDPose: A large-scale trinocular IR Augmented Reality Glasses Pose Dataset
Ahmet Firintepe, Alain Pagani, Didier Stricker
Proc. of. ACM Symposium on Virtual Reality Software and Technology (VRST-2020) ACM 2020 .
- Abstract:
- Augmented Reality Glasses usually implement an Inside-Out tracking. In case of a driving scenario or glasses with less computation capabilities, an Outside-In tracking approach is required. However, to the best of our knowledge, no public datasets exist that collects images of users wearing AR glasses. To address this problem, we present HMDPose, an infrared trinocular dataset of four different AR Head-mounted displays captured in a car. It contains sequences of 14 subjects captured by three different cameras running at 60 FPS each, adding up to more than 3,000,000 labeled images in total. We provide a ground truth 6DoF-pose, captured by a marker-based tracker with submillimeter accuracy. We make this dataset publicly available for non-profit, academic use and non-commercial benchmarking.