P‐105: Sensor‐based Latency Reduction Method for Virtual Reality Head Mounted Display

Seo, Min-Woo; Choi, Song-Woo; Kang, Suk‐Ju

doi:10.1002/sdtp.11954

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Therefore, minimizing the time delay or, at least, keeping the size of the time lag consistent might be critical to reduce the VR sickness. Recently, Seo et al (2017) suggested a sensor-based prediction method to reduce the motion-to-photon latency in an HMD.…”

Section: Latencymentioning

confidence: 99%

Virtual Reality Sickness: A Review of Causes and Measurements

Chang

Kim

Yoo

2020

International Journal of Human–Computer Interaction

585

228

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In virtual reality (VR), users can experience symptoms of motion sickness, which is referred to as VR sickness or cybersickness. The symptoms include but are not limited to eye fatigue, disorientation, and nausea, which can impair the VR experience of users. Though many studies have attempted to reduce the discomfort, they produced conflicting results with varying degrees of VR sickness. In particular, a visually improved VR does not necessarily result in decreased VR sickness. To understand these unexpected results, we surveyed the causes of VR sickness and measurement of symptoms. We reorganized the causes of the VR sickness into three major factors (hardware, content, and human factors) and investigated the sub-component of each factor. We then surveyed frequently used measures of VR sickness, both subjective and objective approaches. We also investigated emerging approaches for reducing VR sickness and proposed a multimodal fidelity hypothesis to give an insight into future studies.

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Section: Latencymentioning

confidence: 99%

Virtual Reality Sickness: A Review of Causes and Measurements

Chang

Kim

Yoo

2020

International Journal of Human–Computer Interaction

585

228

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“…Traditional EKF-and UKF-based algorithms [45], [46] can correct orientation prediction using only accelerometer readings. However, a greater amount of yaw information of orientations can be obtained from magnetometer readings.…”

Section: A Overviewmentioning

confidence: 99%

Orientation Prediction for VR and AR Devices Using Inertial Sensors Based on Kalman-Like Error Compensation

Dao

Nhat

Hong³

et al. 2022

IEEE Access

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We propose an orientation prediction algorithm based on Kalman-like error compensation for virtual reality (VR) and augmented reality (AR) devices using measurements of an inertial measurement unit (IMU), which includes a tri-axial gyroscope and a tri-axial accelerometer. First, the initial prediction of the orientation is estimated by assuming linear movement. Then, to improve the prediction accuracy, the accuracies of previous predictions are taken into account by computing the orientation difference between the current orientation and previous prediction. Finally, we define a weight matrix to determine the optimal adjustments for predictions corresponding to a given orientation, which is obtained by minimizing the estimation errors based on the minimum mean square error (MMSE) criterion using Kalman-like error compensation. Experimental results demonstrate that the proposed algorithm exhibits higher orientation prediction accuracy compared with conventional algorithms on several open datasets.INDEX TERMS Orientation prediction, inertial measurement units (IMUs), motion-to-photon (MTP) latency, virtual reality (VR), augmented reality (AR), attitude and heading reference system (AHRS), minimum mean square error (MMSE).

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P‐105: Sensor‐based Latency Reduction Method for Virtual Reality Head Mounted Display

Cited by 2 publications

References 7 publications

Virtual Reality Sickness: A Review of Causes and Measurements

Virtual Reality Sickness: A Review of Causes and Measurements

Orientation Prediction for VR and AR Devices Using Inertial Sensors Based on Kalman-Like Error Compensation

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