No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior

Sewoong Ahn, Sanghoon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The high performance video quality assessment (VQA) algorithm is a necessary skill to provide high quality video to viewers. However, since the nonlinear perception function between the distortion level of the video and the subjective quality score is not precisely defined, there are many limitations in accurately predicting the quality of the video. In this paper, we propose a deep learning scheme named Deep Blind Video Quality Assessment to achieve a more accurate and reliable video quality predictor by considering various spatial and temporal cues which have not been considered before. We used CNN to extract the spatial cues of each video in VQA and proposed new hand-crafted features for temporal cues. Performance experiments show that performance is better than other state-of-the-art no-reference (NR) VQA models and the introduction of hand-crafted temporal features is very efficient in VQA.

Original languageEnglish
Title of host publication2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1513-1517
Number of pages5
ISBN (Electronic)9789881476852
DOIs
Publication statusPublished - 2019 Mar 4
Event10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, United States
Duration: 2018 Nov 122018 Nov 15

Publication series

Name2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

Conference

Conference10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
CountryUnited States
CityHonolulu
Period18/11/1218/11/15

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Neural networks
Experiments
Deep learning

All Science Journal Classification (ASJC) codes

  • Information Systems

Cite this

Ahn, S., & Lee, S. (2019). No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior. In 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings (pp. 1513-1517). [8659706] (2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/APSIPA.2018.8659706
Ahn, Sewoong ; Lee, Sanghoon. / No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior. 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1513-1517 (2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings).
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Ahn, S & Lee, S 2019, No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior. in 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings., 8659706, 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1513-1517, 10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018, Honolulu, United States, 18/11/12. https://doi.org/10.23919/APSIPA.2018.8659706

No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior. / Ahn, Sewoong; Lee, Sanghoon.

2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1513-1517 8659706 (2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Ahn S, Lee S. No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior. In 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1513-1517. 8659706. (2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings). https://doi.org/10.23919/APSIPA.2018.8659706