IEICE TRANSACTIONS on Information
A Weighted Viewport Quality Metric for Omnidirectional Images
Summary :
Thanks to the ability to bring immersive experiences to users, Virtual Reality (VR) technologies have been gaining popularity in recent years. A key component in VR systems is omnidirectional content, which can provide 360-degree views of scenes. However, at a given time, only a portion of the full omnidirectional content, called viewport, is displayed corresponding to the user's current viewing direction. In this work, we first develop Weighted-Viewport PSNR (W-VPSNR), an objective quality metric for quality assessment of omnidirectional content. The proposed metric takes into account the foveation feature of the human visual system. Then, we build a subjective database consisting of 72 stimuli with spatial varying viewport quality. By using this database, an evaluation of the proposed metric and four conventional metrics is conducted. Experiment results show that the W-VPSNR metric well correlates with the mean opinion scores (MOS) and outperforms the conventional metrics. Also, it is found that the conventional metrics do not perform well for omnidirectional content.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.1 pp.67-70
- Publication Date
- 2020/01/01
- Publicized
- 2019/10/10
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019MUL0002
- Type of Manuscript
- Special Section LETTER (Special Section on Enriched Multimedia — Application of Multimedia Technology and Its Security —)
- Category
Authors
Huyen T. T. TRAN
University of Aizu
Trang H. HOANG
Hanoi University of Science and Technology
Phu N. MINH
Hanoi University of Science and Technology
Nam PHAM NGOC
Vin-University project
Truong CONG THANG
University of Aizu
Keyword
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Huyen T. T. TRAN, Trang H. HOANG, Phu N. MINH, Nam PHAM NGOC, Truong CONG THANG, "A Weighted Viewport Quality Metric for Omnidirectional Images" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 1, pp. 67-70, January 2020, doi: 10.1587/transinf.2019MUL0002.
Abstract: Thanks to the ability to bring immersive experiences to users, Virtual Reality (VR) technologies have been gaining popularity in recent years. A key component in VR systems is omnidirectional content, which can provide 360-degree views of scenes. However, at a given time, only a portion of the full omnidirectional content, called viewport, is displayed corresponding to the user's current viewing direction. In this work, we first develop Weighted-Viewport PSNR (W-VPSNR), an objective quality metric for quality assessment of omnidirectional content. The proposed metric takes into account the foveation feature of the human visual system. Then, we build a subjective database consisting of 72 stimuli with spatial varying viewport quality. By using this database, an evaluation of the proposed metric and four conventional metrics is conducted. Experiment results show that the W-VPSNR metric well correlates with the mean opinion scores (MOS) and outperforms the conventional metrics. Also, it is found that the conventional metrics do not perform well for omnidirectional content.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019MUL0002/_p
Copy
@ARTICLE{e103-d_1_67,
author={Huyen T. T. TRAN, Trang H. HOANG, Phu N. MINH, Nam PHAM NGOC, Truong CONG THANG, },
journal={IEICE TRANSACTIONS on Information},
title={A Weighted Viewport Quality Metric for Omnidirectional Images},
year={2020},
volume={E103-D},
number={1},
pages={67-70},
abstract={Thanks to the ability to bring immersive experiences to users, Virtual Reality (VR) technologies have been gaining popularity in recent years. A key component in VR systems is omnidirectional content, which can provide 360-degree views of scenes. However, at a given time, only a portion of the full omnidirectional content, called viewport, is displayed corresponding to the user's current viewing direction. In this work, we first develop Weighted-Viewport PSNR (W-VPSNR), an objective quality metric for quality assessment of omnidirectional content. The proposed metric takes into account the foveation feature of the human visual system. Then, we build a subjective database consisting of 72 stimuli with spatial varying viewport quality. By using this database, an evaluation of the proposed metric and four conventional metrics is conducted. Experiment results show that the W-VPSNR metric well correlates with the mean opinion scores (MOS) and outperforms the conventional metrics. Also, it is found that the conventional metrics do not perform well for omnidirectional content.},
keywords={},
doi={10.1587/transinf.2019MUL0002},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - A Weighted Viewport Quality Metric for Omnidirectional Images
T2 - IEICE TRANSACTIONS on Information
SP - 67
EP - 70
AU - Huyen T. T. TRAN
AU - Trang H. HOANG
AU - Phu N. MINH
AU - Nam PHAM NGOC
AU - Truong CONG THANG
PY - 2020
DO - 10.1587/transinf.2019MUL0002
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2020
AB - Thanks to the ability to bring immersive experiences to users, Virtual Reality (VR) technologies have been gaining popularity in recent years. A key component in VR systems is omnidirectional content, which can provide 360-degree views of scenes. However, at a given time, only a portion of the full omnidirectional content, called viewport, is displayed corresponding to the user's current viewing direction. In this work, we first develop Weighted-Viewport PSNR (W-VPSNR), an objective quality metric for quality assessment of omnidirectional content. The proposed metric takes into account the foveation feature of the human visual system. Then, we build a subjective database consisting of 72 stimuli with spatial varying viewport quality. By using this database, an evaluation of the proposed metric and four conventional metrics is conducted. Experiment results show that the W-VPSNR metric well correlates with the mean opinion scores (MOS) and outperforms the conventional metrics. Also, it is found that the conventional metrics do not perform well for omnidirectional content.
ER -
English
