Abstract
Abstract One of the main properties of a three-dimensional (3D) video is the large amount of data, which impose challenges for network transport of videos, in applications such as digital video broadcast (DVB), streaming over IP networks, or for transmission over mobile broadband. Addressing these challenges requires a thorough understanding of the characteristics and traffic properties of 3D video formats. We analyzed 3D video formats using publicly available long video frame-size traces of videos in full high definition (HD) resolution with two views. Examined 3D video representation formats are the multiview (MV) video format, the frame sequential (FS) format, and the side-by-side (SBS) format. We performed a multifractal analysis through extensive simulation and showed multifractal properties of 3D video representation formats. It was shown that the MV video had the highest multifractal nature, while the FS video had the lowest. Also, a part of the multifractal spectrum connected to the highest changes in the signal (high bitrate variability) is analyzed in detail. Changes in multifractal properties for different streaming approaches of 3D videos with aggregated frames are examined, as well as the influence of frame types and values of quantization parameters. Multifractal analysis was performed by the method of moments and by the histogram method.
Highlights
A three-dimensional (3D) video contains several views of a video scene, which provide depth perception for a viewer. 3D video representation formats with one frame sequence are labeled as the frame compatible format, ones with two frame sequences are the stereoscopic multiview format, while ones with more video sequences as the multiview video format [1,2,3,4,5].The quantity of data for the multiview video representation format is significantly higher than in the case of the conventional single-view video and presents a restriction on storage and transmission of the video
With multifractal characterization by multifractal spectrum and by generalized dimensions, we found that among the views of the multiview video, the highest burstiness is for the combined view (CV), followed by the left view (LV), being the lowest for the right view (RV)
We analyzed properties of 3D video representation formats: the MV video representation format with multiview video coding and the frame sequential (FS) and the SBS formats coded with a conventional single-view video encoder
Summary
A three-dimensional (3D) video contains several views of a video scene, which provide depth perception for a viewer. 3D video representation formats with one frame sequence are labeled as the frame compatible format, ones with two frame sequences are the stereoscopic multiview format, while ones with more video sequences as the multiview video format [1,2,3,4,5]. The second histogram method has slower convergence of f (α) to f (α) and slower execution, but has a tendency to show additive processes in signal and allows inverse multifractal analysis (determination of the exact part of data with chosen values of pair (α, f (α))). These two methods are different in the way they handle the data, where the method of moments tends to smoothen the data, while the histogram method handles raw data and has less approximation
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