Calibration of Augmented Reality Headset with External Tracking System Using AX=YB

In Augmented Reality, a robust virtual-to-real calibration that aligns the virtual and real spaces is crucial to ensure accurate overlays. Inspired by popular methods in robotics, we propose establishing the virtual-to-real calibration as a hand-eye/robot-world calibration problem using an $A X=Y B$ formulation. This formulation uses both the self-localization of a head-mounted display and the tracking functionality of an external tracking system. Additional techniques are also provided to address the data synchronization issue between the two measurement systems. To further improve the results, we integrate a post-acquisition outlier filter based on the $A X-Y B$ Frobenius norm. Improvements resulting from the filter were first validated by simulation. For the assessment of the complete pipeline, both subjective evaluation based on human perception and objective evaluation based on computer vision methods were used. The results show that the proposed method is accurate and noise-resistant. With only 100 measurement samples collected, the overlay of a tracked object at the farthest distance (1300 mm) in front of the tracking system has an average rotation error of $1.77 \pm 0.54^{\circ}$ and an average translation error of $4.82 \pm 1.71 \mathrm{~mm}$.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/ismar62088.2024.00035
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Calibration of Augmented Reality Headset with External Tracking System Using AX=YB

Alejandro Martin‐Gomez, Mehran Armand, Letian Ai, Yihao Liu
Augmented Reality Applications
article

Calibration of Augmented Reality Headset with External Tracking System Using AX=YB

Alejandro Martin‐Gomez, Mehran Armand, Letian Ai, Yihao Liu
article en

Abstract

In Augmented Reality, a robust virtual-to-real calibration that aligns the virtual and real spaces is crucial to ensure accurate overlays. Inspired by popular methods in robotics, we propose establishing the virtual-to-real calibration as a hand-eye/robot-world calibration problem using an $A X=Y B$ formulation. This formulation uses both the self-localization of a head-mounted display and the tracking functionality of an external tracking system. Additional techniques are also provided to address the data synchronization issue between the two measurement systems. To further improve the results, we integrate a post-acquisition outlier filter based on the $A X-Y B$ Frobenius norm. Improvements resulting from the filter were first validated by simulation. For the assessment of the complete pipeline, both subjective evaluation based on human perception and objective evaluation based on computer vision methods were used. The results show that the proposed method is accurate and noise-resistant. With only 100 measurement samples collected, the overlay of a tracked object at the farthest distance (1300 mm) in front of the tracking system has an average rotation error of $1.77 \pm 0.54^{\circ}$ and an average translation error of $4.82 \pm 1.71 \mathrm{~mm}$.

Johns Hopkins University (US)
National Institutes of Health
Affordable and clean energy
Openalex Percentile: Top 75%
Augmented Reality Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.