No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions
In a 3-D video system, automatically predicting the quality of synthesized 3-D video based on the inputs of color and depth videos is an urgent but very difficult task, while the existing full-reference methods usually measure the perceptual quality of the synthesized video. In this paper, a high-ef...
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sg-ntu-dr.10356-1400312020-05-26T05:12:32Z No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions Shao, Feng Yuan, Qizheng Lin, Weisi Jiang, Gangyi School of Computer Science and Engineering Centre for Multimedia and Network Technology Engineering::Computer science and engineering Color-depth Interactions 3D Synthesized Video In a 3-D video system, automatically predicting the quality of synthesized 3-D video based on the inputs of color and depth videos is an urgent but very difficult task, while the existing full-reference methods usually measure the perceptual quality of the synthesized video. In this paper, a high-efficiency view synthesis quality prediction (HEVSQP) metric for view synthesis is proposed. Based on the derived VSQP model that quantifies the influences of color and depth distortions and their interactions in determining the perceptual quality of 3-D synthesized video, color-involved VSQP and depth-involved VSQP indices are predicted, respectively, and are combined to yield an HEVSQP index. Experimental results on our constructed NBU-3D Synthesized Video Quality Database demonstrate that the proposed HEVSOP has good performance evaluated on the entire synthesized video-quality database, compared with other full-reference and no-reference video-quality assessment metrics. 2020-05-26T05:12:32Z 2020-05-26T05:12:32Z 2017 Journal Article Shao, F., Yuan, Q., Lin, W., & Jiang, G. (2018). No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions. IEEE Transactions on Multimedia, 20(3), 659-674. doi:10.1109/TMM.2017.2748460 1520-9210 https://hdl.handle.net/10356/140031 10.1109/TMM.2017.2748460 2-s2.0-85029157555 3 20 659 674 en IEEE Transactions on Multimedia © 2017 IEEE. All rights reserved. |
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Engineering::Computer science and engineering Color-depth Interactions 3D Synthesized Video Shao, Feng Yuan, Qizheng Lin, Weisi Jiang, Gangyi No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions |
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In a 3-D video system, automatically predicting the quality of synthesized 3-D video based on the inputs of color and depth videos is an urgent but very difficult task, while the existing full-reference methods usually measure the perceptual quality of the synthesized video. In this paper, a high-efficiency view synthesis quality prediction (HEVSQP) metric for view synthesis is proposed. Based on the derived VSQP model that quantifies the influences of color and depth distortions and their interactions in determining the perceptual quality of 3-D synthesized video, color-involved VSQP and depth-involved VSQP indices are predicted, respectively, and are combined to yield an HEVSQP index. Experimental results on our constructed NBU-3D Synthesized Video Quality Database demonstrate that the proposed HEVSOP has good performance evaluated on the entire synthesized video-quality database, compared with other full-reference and no-reference video-quality assessment metrics. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Shao, Feng Yuan, Qizheng Lin, Weisi Jiang, Gangyi |
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Article |
author |
Shao, Feng Yuan, Qizheng Lin, Weisi Jiang, Gangyi |
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Shao, Feng |
title |
No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions |
title_short |
No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions |
title_full |
No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions |
title_fullStr |
No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions |
title_full_unstemmed |
No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions |
title_sort |
no-reference view synthesis quality prediction for 3-d videos based on color-depth interactions |
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2020 |
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https://hdl.handle.net/10356/140031 |
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1681058542973353984 |