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dc.contributor.authorTran, Huyen T. T.
dc.contributor.authorHoang, Trang H.
dc.contributor.authorMinh, Phu N.
dc.contributor.authorPham, Nam N.
dc.contributor.authorTruong, Thang C.
dc.date.accessioned2024-08-18T06:56:45Z
dc.date.available2024-08-18T06:56:45Z
dc.date.issued2020-01-01
dc.identifier.urihttps://vinspace.edu.vn/handle/VIN/175
dc.description.abstractThanks 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.en_US
dc.language.isoenen_US
dc.subjectomnidirectional imagesen_US
dc.subjectobjective quality metricsen_US
dc.titleA Weighted Viewport Quality Metric for Omnidirectional Imagesen_US
dc.typeArticleen_US


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  • Pham Ngoc Nam, PhD [21]
    Vice Dean, College of Engineering and Computer Science - Director, Electrical Engineering program, College of Engineering and Computer Science

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