34,920 research outputs found
Adaptive Quantization Matrices for HD and UHD Display Resolutions in Scalable HEVC
HEVC contains an option to enable custom quantization matrices, which are
designed based on the Human Visual System and a 2D Contrast Sensitivity
Function. Visual Display Units, capable of displaying video data at High
Definition and Ultra HD display resolutions, are frequently utilized on a
global scale. Video compression artifacts that are present due to high levels
of quantization, which are typically inconspicuous in low display resolution
environments, are clearly visible on HD and UHD video data and VDUs. The
default QM technique in HEVC does not take into account the video data
resolution, nor does it take into consideration the associated display
resolution of a VDU to determine the appropriate levels of quantization
required to reduce unwanted video compression artifacts. Based on this fact, we
propose a novel, adaptive quantization matrix technique for the HEVC standard,
including Scalable HEVC. Our technique, which is based on a refinement of the
current HVS-CSF QM approach in HEVC, takes into consideration the display
resolution of the target VDU for the purpose of minimizing video compression
artifacts. In SHVC SHM 9.0, and compared with anchors, the proposed technique
yields important quality and coding improvements for the Random Access
configuration, with a maximum of 56.5% luma BD-Rate reductions in the
enhancement layer. Furthermore, compared with the default QMs and the Sony QMs,
our method yields encoding time reductions of 0.75% and 1.19%, respectively.Comment: Data Compression Conference 201
Objective assessment of region of interest-aware adaptive multimedia streaming quality
Adaptive multimedia streaming relies on controlled
adjustment of content bitrate and consequent video quality variation in order to meet the bandwidth constraints of the communication
link used for content delivery to the end-user. The values of the easy to measure network-related Quality of Service metrics have no direct relationship with the way moving images are
perceived by the human viewer. Consequently variations in the video stream bitrate are not clearly linked to similar variation in the user perceived quality. This is especially true if some human visual system-based adaptation techniques are employed. As research has shown, there are certain image regions in each frame of a video sequence on which the users are more interested than in the others. This paper presents the Region of Interest-based Adaptive Scheme (ROIAS) which adjusts differently the regions within each frame of the streamed multimedia content based on the user interest in them. ROIAS is presented and discussed in terms of the adjustment algorithms employed and their impact on the human perceived video quality. Comparisons with existing approaches, including a constant quality adaptation scheme across the whole frame area, are performed employing two objective metrics which estimate user perceived video quality
Dynamic Adaptive Point Cloud Streaming
High-quality point clouds have recently gained interest as an emerging form
of representing immersive 3D graphics. Unfortunately, these 3D media are bulky
and severely bandwidth intensive, which makes it difficult for streaming to
resource-limited and mobile devices. This has called researchers to propose
efficient and adaptive approaches for streaming of high-quality point clouds.
In this paper, we run a pilot study towards dynamic adaptive point cloud
streaming, and extend the concept of dynamic adaptive streaming over HTTP
(DASH) towards DASH-PC, a dynamic adaptive bandwidth-efficient and view-aware
point cloud streaming system. DASH-PC can tackle the huge bandwidth demands of
dense point cloud streaming while at the same time can semantically link to
human visual acuity to maintain high visual quality when needed. In order to
describe the various quality representations, we propose multiple thinning
approaches to spatially sub-sample point clouds in the 3D space, and design a
DASH Media Presentation Description manifest specific for point cloud
streaming. Our initial evaluations show that we can achieve significant
bandwidth and performance improvement on dense point cloud streaming with minor
negative quality impacts compared to the baseline scenario when no adaptations
is applied.Comment: 6 pages, 23rd ACM Packet Video (PV'18) Workshop, June 12--15, 2018,
Amsterdam, Netherland
Data compression techniques applied to high resolution high frame rate video technology
An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended
Quality of experience driven control of interactive media stream parameters
In recent years, cloud computing has led to many new kinds of services. One of these popular services is cloud gaming, which provides the entire game experience to the users remotely from a server, but also other applications are provided in a similar manner. In this paper we focus on the option to render the application in the cloud, thereby delivering the graphical output of the application to the user as a video stream. In more general terms, an interactive media stream is set up over the network between the user's device and the cloud server. The main issue with this approach is situated at the network, that currently gives little guarantees on the quality of service in terms of parameters such as available bandwidth, latency or packet loss. However, for interactive media stream cases, the user is merely interested in the perceived quality, regardless of the underlaying network situation. In this paper, we present an adaptive control mechanism that optimizes the quality of experience for the use case of a race game, by trading off visual quality against frame rate in function of the available bandwidth. Practical experiments verify that QoE driven adaptation leads to improved user experience compared to systems solely taking network characteristics into account
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