Multi-Feature 360 Video Quality Estimation
| Autor: | Roberto G. de A. Azevedo, Neil Birkbeck, Ivan Janatra, Balu Adsumilli, Pascal Frossard |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | IEEE Open Journal of Circuits and Systems, Vol 2, Pp 338-349 (2021) |
| Druh dokumentu: | article |
| ISSN: | 2644-1225 27522318 |
| DOI: | 10.1109/OJCAS.2021.3073891 |
| Popis: | We propose a new method for the visual quality assessment of 360-degree (omnidirectional) videos. The proposed method is based on computing multiple spatio-temporal objective quality features on viewports extracted from 360-degree videos. A new model is learnt to properly combine these features into a metric that closely matches subjective quality scores. The main motivations for the proposed approach are that: 1) quality metrics computed on viewports better captures the user experience than metrics computed on the projection domain; 2) the use of viewports easily supports different projection methods being used in current 360-degree video systems; and 3) no individual objective image quality metric always performs the best for all types of visual distortions, while a learned combination of them is able to adapt to different conditions. Experimental results, based on both the largest available 360-degree videos quality dataset and a cross-dataset validation, demonstrate that the proposed metric outperforms state-of-the-art 360-degree and 2D video quality metrics. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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