Multi-pooled Inception Features for No-reference Video Quality Assessment

Domonkos Varga

Abstract

Video quality assessment (VQA) is an important element of a broad spectrum of applications ranging from automatic video streaming to surveillance systems. Furthermore, the measurement of video quality requires an extensive investigation of image and video features. In this paper, we introduce a novel feature extraction method for no-reference video quality assessment (NR-VQA) relying on visual features extracted from multiple Inception modules of pretrained convolutional neural networks (CNN). Hence, we show a solution which incorporates both intermediate- and high-level deep representations from a CNN to predict digital videos’ perceptual quality. Second, we demonstrate that processing all frames of a video to be evaluated is unnecessary and examining only the so-called intra-frames saves computational time and improves performance significantly. The proposed architecture was trained and tested on the recently published KoNViD-1k database.

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Paper Citation


in Harvard Style

Varga D. (2020). Multi-pooled Inception Features for No-reference Video Quality Assessment.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-402-2, pages 338-347. DOI: 10.5220/0008978503380347


in Bibtex Style

@conference{visapp20,
author={Domonkos Varga},
title={Multi-pooled Inception Features for No-reference Video Quality Assessment},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2020},
pages={338-347},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008978503380347},
isbn={978-989-758-402-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Multi-pooled Inception Features for No-reference Video Quality Assessment
SN - 978-989-758-402-2
AU - Varga D.
PY - 2020
SP - 338
EP - 347
DO - 10.5220/0008978503380347