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Comparison of Subjective Quality Evaluation for HEVC Encoded Omnidirectional Videos at Different Bit-rates for UHD and FHD Resolution

Published:23 October 2017Publication History

ABSTRACT

In this paper, we perform subjective quality evaluation studies for HEVC/H.265-encoded omnidirectional videos at different bit-rates for two different resolutions (FHD and UHD) on an Oculus Rift. Results of these tests provide insight into appropriate coding and resolution settings for given bitrate constraints, for example in an HTTP-based streaming (HAS) context. Subjective quality judgements were collected on a 5-point Absolute Category Rating (ACR) scale. Further, we collected head motion data during viewing and rating. Working towards the technical goal of subjective evaluation for different resolutions and bit-rates, we address aspects of how to conduct respective viewing tests, involving information from head-rotation tracking (yaw and pitch) and motion-sickness questionnaires. Quality adaptation (in terms of resolution and bit-rate) of omnidirectional videos is an important feature of media streaming. Its effect on subjective quality evaluations of 360° video has not been investigated so far. To utilize network and processing resources efficiently, limitations in the resolution of current Head Mounted Displays (HMDs), with typically 2160 x 1200 pixels per view, may be exploited. The subjective test results provide indications for boundaries between resolution and quantization scaling. To discuss the merits of the applied subjective test method, we compare simulator sickness scores along with behavioral data.

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  1. Comparison of Subjective Quality Evaluation for HEVC Encoded Omnidirectional Videos at Different Bit-rates for UHD and FHD Resolution

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            cover image ACM Conferences
            Thematic Workshops '17: Proceedings of the on Thematic Workshops of ACM Multimedia 2017
            October 2017
            558 pages
            ISBN:9781450354165
            DOI:10.1145/3126686

            Copyright © 2017 ACM

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            Publication History

            • Published: 23 October 2017

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