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On the Effectiveness of Offset Projections for 360-Degree Video Streaming

Published:15 June 2018Publication History
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Abstract

A new generation of video streaming technology, 360-degree video, promises greater immersiveness than standard video streams. This level of immersiveness is similar to that produced by virtual reality devices—users can control the field of view using head movements rather than needing to manipulate external devices. Although 360-degree video could revolutionize the streaming experience, its large-scale adoption is hindered by a number of factors: 360-degree video streams have larger bandwidth requirements and require faster responsiveness to user inputs, and users may be more sensitive to lower quality streams.

In this article, we review standard approaches toward 360-degree video encoding and compare these to families of approaches that distort the spherical surface to allow oriented concentrations of the 360-degree view. We refer to these distorted projections as offset projections. Our measurement studies show that most types of offset projections produce rendered views with better quality than their nonoffset equivalents when view orientations are within 40 or 50 degrees of the offset orientation. Offset projections complicate adaptive 360-degree video streaming because they require a combination of bitrate and view orientation adaptations. We estimate that this combination of streaming adaptation in two dimensions can cause over 57% extra segments to be downloaded compared to an ideal downloading strategy, wasting 20% of the total downloading bandwidth.

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      • Published in

        cover image ACM Transactions on Multimedia Computing, Communications, and Applications
        ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 14, Issue 3s
        Special Section on Delay-Sensitive Video Computing in the Cloud and Special Section on Extended MMSys-NOSSDAV Best Papers
        June 2018
        317 pages
        ISSN:1551-6857
        EISSN:1551-6865
        DOI:10.1145/3233173
        Issue’s Table of Contents

        Copyright © 2018 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 15 June 2018
        • Accepted: 1 April 2018
        • Revised: 1 March 2018
        • Received: 1 October 2017
        Published in tomm Volume 14, Issue 3s

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