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User-perceived quality aware adaptive streaming of 3D multi-view video plus depth over the internet

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Abstract

Video streaming is a foremost and growing contributor in the ever increasing Internet traffic. Since last two decades, due to the enhancement in cameras and image processing technology, we have seen a shift towards multi-view plus depth (MVD) technology from traditional 2D and 3D video technology. This growth comes with deep changes in the Internet bandwidth, video coding and network technologies, which smoothed the mode for delivery of MVD content to end-users over the Internet. Since, MVD contains large amounts of data than single view video, it requires more bandwidth. It is a challenging task for network service provider to deliver such views with the best user’s Quality of Experience(QoE) in dynamic network condition. Also, Internet is known to be prone to packet loss, bandwidth variation, delay and network congestion, which may prevent video packets from being delivered on time. Besides that, different capabilities of end user’s devices in terms of computing power, display, and access link capacity are other challenges. As consequences, the viewing experiences of 3D videos may well degrade, if the quality-aware adaptation techniques are not deployed. In this article, our work concentrates to present a comprehensive analysis of a dynamic network environment for streaming of 3D MVD over Internet (HTTP). We analyzed the effect of different adaptation of decision strategies and formulated a new quality-aware adaptation technique. The proposed technique is promoting from layer based video coding in terms of transmitted views scalability. The results of MVD streaming experiment, using the proposed approach have shown that the video quality of perceptual 3D improves significantly, as an effect of proposed quality aware adaptation even in adverse network conditions.

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Correspondence to Nabin Kumar Karn.

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Karn, N.K., Zhang, H. & Jiang, F. User-perceived quality aware adaptive streaming of 3D multi-view video plus depth over the internet. Multimed Tools Appl 77, 22965–22983 (2018). https://doi.org/10.1007/s11042-018-5744-8

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