Outside-in monocular IR camera based HMD pose estimation via geometric optimization

Pavel A. Savkin; Shunsuke Saito; Jarich Vansteenberge; Tsukasa Fukusato; Lochlainn Wilson; Shigeo Morishima

doi:10.1145/3139131.3139136

Outside-in monocular IR camera based HMD pose estimation via geometric optimization

Pavel A. Savkin, Shunsuke Saito, Jarich Vansteenberge, Tsukasa Fukusato, Lochlainn Wilson, Shigeo Morishima

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Accurately tracking a Head Mounted Display (HMD) with a 6 degree of freedom is essential to achieve a comfortable and a nausea free experience in Virtual Reality. Existing commercial HMD systems using synchronized Infrared (IR) camera and blinking IR-LEDs can achieve highly accurate tracking. However, most of the o-the-shelf cameras do not support frame synchronization. In this paper, we propose a novel method for real time HMD pose estimation without using any camera synchronization or LED blinking. We extended over the state of the art pose estimation algorithm by introducing geometrically constrained optimization. In addition, we propose a novel system to increase robustness to the blurred IR-LEDs paerns appearing at high-velocity movements. The quantitative evaluations showed signicant improvements in pose stability and accuracy over wide rotational movements as well as a decrease in runtime.

Original language	English
Title of host publication	Proceedings - VRST 2017
Subtitle of host publication	23rd ACM Conference on Virtual Reality Software and Technology
Publisher	Association for Computing Machinery
Volume	Part F131944
ISBN (Electronic)	9781450355483
DOIs	https://doi.org/10.1145/3139131.3139136
Publication status	Published - 2017 Nov 8
Event	23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017 - Gothenburg, Sweden Duration: 2017 Nov 8 → 2017 Nov 10

Other

Other	23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017
Country	Sweden
City	Gothenburg
Period	17/11/8 → 17/11/10

Keywords

Monocular IR camera
Perspective-n-Point problem
Position tracking
Vision-based pose estimation

ASJC Scopus subject areas

Software

Access to Document

10.1145/3139131.3139136

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Savkin, P. A., Saito, S., Vansteenberge, J., Fukusato, T., Wilson, L., & Morishima, S. (2017). Outside-in monocular IR camera based HMD pose estimation via geometric optimization. In Proceedings - VRST 2017: 23rd ACM Conference on Virtual Reality Software and Technology (Vol. Part F131944). [a7] Association for Computing Machinery. https://doi.org/10.1145/3139131.3139136

Outside-in monocular IR camera based HMD pose estimation via geometric optimization. / Savkin, Pavel A.; Saito, Shunsuke; Vansteenberge, Jarich; Fukusato, Tsukasa; Wilson, Lochlainn; Morishima, Shigeo.

Proceedings - VRST 2017: 23rd ACM Conference on Virtual Reality Software and Technology. Vol. Part F131944 Association for Computing Machinery, 2017. a7.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Savkin, PA, Saito, S, Vansteenberge, J, Fukusato, T, Wilson, L & Morishima, S 2017, Outside-in monocular IR camera based HMD pose estimation via geometric optimization. in Proceedings - VRST 2017: 23rd ACM Conference on Virtual Reality Software and Technology. vol. Part F131944, a7, Association for Computing Machinery, 23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017, Gothenburg, Sweden, 17/11/8. https://doi.org/10.1145/3139131.3139136

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abstract = "Accurately tracking a Head Mounted Display (HMD) with a 6 degree of freedom is essential to achieve a comfortable and a nausea free experience in Virtual Reality. Existing commercial HMD systems using synchronized Infrared (IR) camera and blinking IR-LEDs can achieve highly accurate tracking. However, most of the o-the-shelf cameras do not support frame synchronization. In this paper, we propose a novel method for real time HMD pose estimation without using any camera synchronization or LED blinking. We extended over the state of the art pose estimation algorithm by introducing geometrically constrained optimization. In addition, we propose a novel system to increase robustness to the blurred IR-LEDs paerns appearing at high-velocity movements. The quantitative evaluations showed signicant improvements in pose stability and accuracy over wide rotational movements as well as a decrease in runtime.",

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