85 research outputs found
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
Increasing the User Experience of Multimedia Presentations with Sensory Effects",
ABSTRACT The term Universal Multimedia Experience (UME) has gained momentum and is well recognized within the research community. As this approach puts the user into the center stage, additional complexity is added to the overall quality assessment problem which calls for a scientific framework to capture, measure, quantify, judge, and INTRODUCTION The Universal Multimedia Experience (UME) is nowadays well known within the research community and has been derived from Universal Multimedia Access (UMA) The remainder of this paper is organized as follows. Section 2 describes the Sensory Effect Media Player (SEMP) which has been developed in order to conduct the subjective tests. Section 3 provides the actual test environment including the extended test procedure and the evaluation results. Conclusions and future work items are presented in Section 4. SENSORY EFFECT MEDIA PLAYER The Sensory Effect Media Player (SEMP) is a DirectShowbased media player with support for the Sensory Effect Description Language (SEDL) as defined i
Improving the Quality of Multimedia Experience through Sensory Effects. In:
ABSTRACT In previous and related work sensor
Scalable Video Coding Guidelines and Performance Evaluations for Adaptive Media Delivery of High Definition Content
International audienceScalability within media coding allows for content adaptation towards heterogeneous user contexts and enables in-network adaptation. However, there is no straightforward solution how to encode the content in a scalable way while maximizing rate-distortion performance. In this paper we provide encoding guidelines for scalable video coding based on a survey of media streaming industry solutions and a comprehensive performance evaluation using four state of the art scalable video codecs with a focus on high-definition content (1080p)
Innovation Mashups: Academic Rigor Meets Social Networking Buzz
Exploring new options for publishing and content delivery offers an enormous opportunity to improve the state of the art and further modernize academic and professional publications.
Traditional organizations such as the IEEE Computer Society, ACM, and Usenix have been encountering increasing competition from new ways of rapid publishing and dissemination, including social networking sites (Facebook, Twitter, LinkedIn, Google+), blogs with enabled commenting, video posting (YouTube), Slashdot, and many other types of media. Liking is replacing traditional impact factors, comments left on authors\u27 webpages or blogs are replacing formal reviews, and site visits have more relevance than the number of article citations
Bitrate Ladder Prediction Methods for Adaptive Video Streaming: A Review and Benchmark
HTTP adaptive streaming (HAS) has emerged as a widely adopted approach for
over-the-top (OTT) video streaming services, due to its ability to deliver a
seamless streaming experience. A key component of HAS is the bitrate ladder,
which provides the encoding parameters (e.g., bitrate-resolution pairs) to
encode the source video. The representations in the bitrate ladder allow the
client's player to dynamically adjust the quality of the video stream based on
network conditions by selecting the most appropriate representation from the
bitrate ladder. The most straightforward and lowest complexity approach
involves using a fixed bitrate ladder for all videos, consisting of
pre-determined bitrate-resolution pairs known as one-size-fits-all. Conversely,
the most reliable technique relies on intensively encoding all resolutions over
a wide range of bitrates to build the convex hull, thereby optimizing the
bitrate ladder for each specific video. Several techniques have been proposed
to predict content-based ladders without performing a costly exhaustive search
encoding. This paper provides a comprehensive review of various methods,
including both conventional and learning-based approaches. Furthermore, we
conduct a benchmark study focusing exclusively on various learning-based
approaches for predicting content-optimized bitrate ladders across multiple
codec settings. The considered methods are evaluated on our proposed
large-scale dataset, which includes 300 UHD video shots encoded with software
and hardware encoders using three state-of-the-art encoders, including
AVC/H.264, HEVC/H.265, and VVC/H.266, at various bitrate points. Our analysis
provides baseline methods and insights, which will be valuable for future
research in the field of bitrate ladder prediction. The source code of the
proposed benchmark and the dataset will be made publicly available upon
acceptance of the paper
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