no reference quality assessment.pdf (2.11 MB)
No reference quality assessment of stereo video based on saliency and sparsity
journal contribution
posted on 2018-09-10, 08:51 authored by Jiachen Yang, Chunqi Ji, Bin Jiang, Wen Lu, Qinggang MengQinggang MengWith the popularity of video technology, stereoscopic video quality assessment (SVQA) has become increasingly important. Existing SVQA methods cannot achieve good performance because the videos' information is not fully utilized. In this paper, we consider various information in the videos together, construct a simple model to combine and analyze the diverse features, which is based on saliency and sparsity. First, we utilize the 3-D saliency map of sum map, which remains the basic information of stereoscopic video, as a valid tool to evaluate the videos' quality. Second, we use the sparse representation to decompose the sum map of 3-D saliency into coefficients, then calculate the features based on sparse coefficients to obtain the effective expression of videos' message. Next, in order to reduce the relevance between the features, we put them into stacked auto-encoder, mapping vectors to higher dimensional space, and adding the sparse restraint, then input them into support vector machine subsequently, and finally, get the quality assessment scores. Within that process, we take the advantage of saliency and sparsity to extract and simplify features. Through the later experiment, we can see the proposed method is fitting well with the subjective scores.
Funding
This work was supported in part by the National Natural Science Foundation of China under Grant 61471260, and in part by the Natural Science Foundation of Tianjin under Grant 16JCYBJC16000.
History
School
- Science
Department
- Computer Science
Published in
IEEE Transactions on BroadcastingVolume
64Issue
2Pages
341 - 353Citation
YANG, J. ... et al, 2018. No reference quality assessment of stereo video based on saliency and sparsity. IEEE Transactions on Broadcasting, 64 (2), pp.341-353.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Acceptance date
2017-12-20Publication date
2018-02-28Notes
© 2018 IEEE. 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.ISSN
0018-9316eISSN
1557-9611Publisher version
Language
- en