No-reference quality assessment of stereoscopic videos with inter-frame cross on a content-rich database
journal contribution
posted on 2021-03-23, 11:41 authored by Jiachen Yang, Yang Zhao, Bin Jiang, Qinggang MengQinggang Meng, Wen Lu, Xinbo Gao© 1991-2012 IEEE. With the wide application of stereoscopic video technology, the quality of stereoscopic video has attracted people's attention. Objective stereoscopic video quality assessment (SVQA) is highly challenging, but essential, particularly the no-reference (NR) SVQA method, where reference information is not needed and a large number of samples are required for training and testing sets. However, as far as we know, there are only a few samples in the established stereo video database, which is unsuitable for NR quality assessment and seriously hampers the development of NR-SVQA method. For these difficulties that we encountered, we carry out a comprehensive subjective evaluation of stereoscopic video quality in our newly established TJU-SVQA databases that contain various contents, mixed resolution coding and symmetrically/asymmetrically distorted stereoscopic videos. Furthermore, we propose a new inter-frame cross map to predict the objective quality scores. We compare and analyze the performance of several state-of-the-art 2D and 3D quality evaluation methods on our new databases. The experimental results on our established databases and a public database demonstrate that the proposed method can robustly predict the quality of stereoscopic videos.
Funding
National Natural Science Foundation of China (No. 61871283)
Foundation of Pre-Research on Equipment of China (NO.61403120103)
Major Civil-Military Integration Project in Tianjin, China (NO.18ZXJMTG00170)
History
School
- Science
Department
- Computer Science
Published in
IEEE Transactions on Circuits and Systems for Video TechnologyVolume
30Issue
10Pages
3608 - 3623Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2019-10-10Publication date
2019-10-21Copyright date
2020ISSN
1051-8215eISSN
1558-2205Publisher version
Language
- en
Depositor
Prof Qinggang Meng. Deposit date: 18 March 2021Usage metrics
Keywords
VideosDatabasesThree-dimensional displaysQuality assessmentStereo image processingDistortionStereoscopic video quality assessmentinter-frame crossTJU-SVQA databaseScience & TechnologyTechnologyEngineering, Electrical & ElectronicEngineeringPREDICTIONPHASEArtificial Intelligence & Image ProcessingElectrical and Electronic EngineeringArtificial Intelligence and Image Processing
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