TY - GEN
T1 - Outside-in monocular IR camera based HMD pose estimation via geometric optimization
AU - Savkin, Pavel A.
AU - Saito, Shunsuke
AU - Vansteenberge, Jarich
AU - Fukusato, Tsukasa
AU - Wilson, Lochlainn
AU - Morishima, Shigeo
N1 - Funding Information:
Pavel A. Savkin is the inventor and applicant of a patent application relevant to this work (JP-2016-253835). is work was supported by JST ACCEL Grant Number JPMJAC1602, Japan.
Publisher Copyright:
© 2017 ACM.
PY - 2017/11/8
Y1 - 2017/11/8
N2 - 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.
AB - 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.
KW - Monocular IR camera
KW - Perspective-n-Point problem
KW - Position tracking
KW - Vision-based pose estimation
UR - http://www.scopus.com/inward/record.url?scp=85038598391&partnerID=8YFLogxK
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U2 - 10.1145/3139131.3139136
DO - 10.1145/3139131.3139136
M3 - Conference contribution
AN - SCOPUS:85038598391
T3 - Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST
BT - Proceedings - VRST 2017
A2 - Spencer, Stephen N.
PB - Association for Computing Machinery
T2 - 23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017
Y2 - 8 November 2017 through 10 November 2017
ER -