NDLI: Visual Quality and File Size Prediction of H.264 Videos and Its Application to Video Transcoding for the Multimedia Messaging Service and Video on Demand

Content Provider	IEEE Xplore Digital Library
Author	Joset, D. Coulombe, S.
Copyright Year	2013
Description	Author affiliation: Dept. of Software & IT Eng., Univ. du Quebec Montreal, Montreal, QC, Canada (Joset, D.; Coulombe, S.)
Abstract	In this paper, we address the problem of adapting video files to meet terminal file size and resolution constraints while maximizing visual quality. First, two new quality estimation models are proposed, which predict quality as function of resolution, quantization step size, and frame rate parameters. The first model is generic and the second takes video motion into account. Then, we propose a video file size estimation model. Simulation results show a Pearson correlation coefficient (PCC) of 0.956 between the mean opinion score and our generic quality model (0.959 for the motion-conscious model). We obtain a PCC of 0.98 between actual and estimated file sizes. Using these models, we estimate the combination of parameters that yields the best video quality while meeting the target terminal's constraints. We obtain an average quality difference of 4.39% (generic model) and of 3.22% (motion-conscious model) when compared with the best theoretical transcoding possible. The proposed models can be applied to video transcoding for the Multimedia Messaging Service and for video on demand services such as YouTube and Netflix.
Starting Page	321
Ending Page	328
File Size	447323
Page Count	8
File Format	PDF
e-ISBN	9781479921713
DOI	10.1109/ISM.2013.62
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Videos Visualization Estimation Quantization (signal) Adaptation models Computational modeling Training video on demand Visual quality assessment predictive models H.264 video transcoding Multimedia Messaging Service
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Subjective assessment of h.264/avc video for low-bitrate multimedia messaging services (2004).

Fast block size prediction for MPEG-2 to H.264/AVC transcoding

Impact of RLC losses on quality prediction for H.264 video over UMTS networks

Fast H.264 to HEVC transcoder based on post-order traversal of quadtree structure

Quality-efficient de-interlacing for H.264-coded videos

Error-Resilience Transcoding of H.264/AVC Compressed Videos

Adaptive transform size and frame-field selection for efficient VC-1 to H.264 high profile transcoding

No-Reference Video Quality Assessment using MPEG analysis

Subjective assessment of H.264-AVC video for low-bitrate multimedia messaging services

Visual Quality and File Size Prediction of H.264 Videos and Its Application to Video Transcoding for the Multimedia Messaging Service and Video on Demand

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