Video adaptation for mobile digital television

Mobile digital television is one of the new services introduced recently by telecommunications operators in the market. Due to the possibilities of personalization and interaction provided, together with the increasing demand of this type of portable services, it would be expected to be a successful technology in near future. Video contents stored and transmitted over the networks deployed to provide mobile digital television need to be compressed to reduce the resources required. The compression scheme chosen by the great majority of these networks is H.264/AVC. Compressed video bitstreams have to be adapted to heterogeneous networks and a wide range of terminals. To deal with this problem scalable video coding schemes were proposed and standardized providing temporal, spatial and quality scalability using layers within the encoded bitstream. Because existing H.264/AVC contents cannot benefit from scalability tools, efficient techniques for migration of single-layer to scalable contents are desirable for supporting these mobile digital television systems. This paper proposes a technique to convert from single-layer H.264/AVC bitstream to a scalable bitstream with temporal scalability. Applying this approach, a reduction of 60% of coding complexity is achieved while maintaining the coding efficiency

On an evaluation of transformation languages in a fully XML-driven framework for video content adaptation

Bitstream Structure Descriptions (BSDs) allow taking the complexity of transforming scalable bitstreams from the compressed domain to the semantic domain. These descriptions are an essential part of an XUL-driven video adaptation framework. The performance of a BSD transformation engine is very important in such an architecture. This paper evaluates the efficiency of XML-based transformation languages in our video adaptation framework. XSLT, STX, and a hybrid solution are compared to each other in terms of execution times, memory consumption, and user-friendliness. Our experiments show that STX is the preferred solution when speed and low-memory are important. The hybrid solution is competitive in terms of memory consumption and is more user-friendly than STX. Although XSLT is relative fast, its memory consumption is very high

A perceptual comparison of empirical and predictive region-of-interest video

When viewing multimedia presentations, a user only attends to a relatively small part of the video display at any one point in time. By shifting allocation of bandwidth from peripheral areas to those locations where a user’s gaze is more likely to rest, attentive displays can be produced. Attentive displays aim to reduce resource requirements while minimizing negative user perception—understood in this paper as not only a user’s ability to assimilate and understand information but also his/her subjective satisfaction with the video content. This paper introduces and discusses a perceptual comparison between two region-of-interest display (RoID) adaptation techniques. A RoID is an attentive display where bandwidth has been preallocated around measured or highly probable areas of user gaze. In this paper, video content was manipulated using two sources of data: empirical measured data (captured using eye-tracking technology) and predictive data (calculated from the physical characteristics of the video data). Results show that display adaptation causes significant variation in users’ understanding of specific multimedia content. Interestingly, RoID adaptation and the type of video being presented both affect user perception of video quality. Moreover, the use of frame rates less than 15 frames per second, for any video adaptation technique, caused a significant reduction in user perceived quality, suggesting that although users are aware of video quality reduction, it does impact level of information assimilation and understanding. Results also highlight that user level of enjoyment is significantly affected by the type of video yet is not as affected by the quality or type of video adaptation—an interesting implication in the field of entertainment

Seamless video access for mobile devices by content-aware utility-based adaptation

Today's Internet multimedia services are characterized by heterogeneous networks, a wide range of terminals, diverse user preferences, and varying natural environment conditions. Heterogeneity of terminals, networks, and user preferences impose nontrivial challenges to the Internet multimedia services for providing seamless multimedia access particularly for mobile devices (e.g., laptops, tablet PCs, PDAs, mobile phones, etc.). Thus, it is essential that advanced multimedia technologies are developed to deal with these challenges. One of these technologies is video adaptation, which has gained significant importance with its main objective of enabling seamless access to video contents available over the Internet. Adaptation decision taking, which can be considered as the "brain" of video adaptation, assists video adaptation to achieve this objective. Scalable Video Coding (SVC) offers flexibility for video adaptation through providing a comprehensive set of scalability parameters (i.e., temporal, spatial, and quality) for producing scalable video streams. Deciding the best combination of scalability parameters to adapt a scalable video stream while satisfying a set of constraints (e.g., device specifics, network bandwidth, etc.) poses challenges for the existing adaptation services to enable seamless video access. To ease such challenges, an adaptation decision taking technique employing a utility-based approach to decide on the most adequate scalability parameters for adaptation operations is developed. A Utility Function (UF), which models the relationships among the scalability parameters and weights specifying the relative importance of these parameters considering video content characteristics (i.e., motion activity and structural feature), is proposed to assist the developed technique. In order to perform the developed adaptation decision taking technique, a video adaptation framework is also proposed in this paper. The adaptation experiments performed using the proposed framework prove the effectiveness of the framework to provide an important step towards enabling seamless video access for mobile devices to enhance viewing experience of users. © 2012 Springer Science+Business Media, LLC

Video Adaptation for High-Quality Content Delivery

Modern video players employ complex algorithms to adapt the bitrate of the video that is shown to the user. Bitrate adaptation requires a tradeoff between reducing the probability that the video freezes (rebuffers) and enhancing the quality of the video. A bitrate that is too high leads to frequent rebuffering, while a bitrate that is too low leads to poor video quality. In this dissertation we propose video-adaptation algorithms to deliver content and maximize the viewer\u27s quality of experience (QoE). Video providers partition videos into short segments and encode each segment at multiple bitrates. The video player adaptively chooses the bitrate of each segment to download, possibly choosing different bitrates for successive segments. We formulate bitrate adaptation as a utility-maximization problem, and design algorithms to provide provably near-optimal time-average utility. Real-world systems are generally too complex to be fully represented in a theoretical model and thus present a new set of challenges. We design algorithms that deliver video on production systems, maintaining the strengths of the theoretical algorithms while also tackling challenges faced in production. Our algorithms are now part of the official DASH reference player dash.js and are being used by video providers in production environments. Most online video is streamed via HTTP over TCP. TCP provides reliable delivery at the expense of additional latency incurred when retransmitting lost packets and head-of-line blocking. Using QUIC allows the video player to tolerate some packet loss without incurring the performance penalties. We design and implement algorithms that exploit this added flexibility to provide higher overall QoE by reducing latency and rebuffering while allowing some packet loss. Recently virtual reality content is increasing in popularity, and delivering 360° video comes with new challenges and opportunities. The viewing space is often partitioned in tiles, and a viewer using a head-mounted display only sees a subset of the tiles at any time. We develop an open source simulation environment for fast and reproducible testing of 360° algorithms. We develop adaptation algorithms that provide high QoE by allocating more bandwidth resources to deliver the tiles that the viewer is more likely to see, while ensuring that the video player reacts in a timely manner when the viewer changes their head pose

Efficient HEVC-based video adaptation using transcoding

In a video transmission system, it is important to take into account the great diversity of the network/end-user constraints. On the one hand, video content is typically streamed over a network that is characterized by different bandwidth capacities. In many cases, the bandwidth is insufficient to transfer the video at its original quality. On the other hand, a single video is often played by multiple devices like PCs, laptops, and cell phones. Obviously, a single video would not satisfy their different constraints. These diversities of the network and devices capacity lead to the need for video adaptation techniques, e.g., a reduction of the bit rate or spatial resolution. Video transcoding, which modifies a property of the video without the change of the coding format, has been well-known as an efficient adaptation solution. However, this approach comes along with a high computational complexity, resulting in huge energy consumption in the network and possibly network latency. This presentation provides several optimization strategies for the transcoding process of HEVC (the latest High Efficiency Video Coding standard) video streams. First, the computational complexity of a bit rate transcoder (transrater) is reduced. We proposed several techniques to speed-up the encoder of a transrater, notably a machine-learning-based approach and a novel coding-mode evaluation strategy have been proposed. Moreover, the motion estimation process of the encoder has been optimized with the use of decision theory and the proposed fast search patterns. Second, the issues and challenges of a spatial transcoder have been solved by using machine-learning algorithms. Thanks to their great performance, the proposed techniques are expected to significantly help HEVC gain popularity in a wide range of modern multimedia applications

Post Your Version Here! : Performances in/of Online, Noncommercial, Video-to-Video Adaptations

Processes of creative adaptation no longer fit traditional, culturally sanctioned forms, like commercial book-to-film adaptation, or vice versa. Meanwhile, internet users are demonstrating how noncommercial, creative text adaptation using video technology has become an everyday art form, a skill set, a form of communication, and a means of cultural commentary. Internet video adapters physically perform in their own videos and they create videos that work performatively online. Negotiating the slippery spaces between copyright, creativity, and cultural commentary, these creators adapt videos in myriad ways, and find spaces to share their adaptations online, despite (for most) a lack of financial return for their creative work. Yet, little scholarship addresses this type of online adaptation. Current studies of internet video memes do not explicitly address how memes work as adaptation or as performance. We are also at a loss for theories about adaptation and performance that serve contemporary, internet-literate publics. In this dissertation, I explore how traditional notions of the processes and products of adaptation are changing. I argue that internet video memes and “sweded” videos are performances of adaptation. Focusing on four case studies, each of which represents types of adaptations that do not fit well into current adaptation theories, I develop a typology for online video-to-video adaptation that could be useful in multidisciplinary or interdisciplinary academic and/or public conversations. Using this typology, I map some of the (mostly uncharted) terrain of online video adaptation performances, elucidate the limits of and expand upon contemporary theories of adaptation, and clarify some major problems and paradoxes of current US copyright law, as it pertains to online video adaptation. Throughout, I show how the adaptations in this study create, sustain, and/or upend contemporary culture, concluding that most (if not all) online video-to-video adaptation trends carry creative potential, along with potential ethical quandaries

Improving scalable video adaptation in a knowledge-based framework

In a knowledge-based content adaptation framework, video adaptation can be performed in a series of steps, named conversions. The high-level decision phase in such a framework occasionally encounters several feasible parameter values of a specific conversion. This paper proposes to transfer further decisions to a low-level phase that decides which parameters maximise the quality of the adaptation. Particularly when more than one solution are available, an innovative quality measure is used for selecting the best values for the parameters among the set of values that fulfil the adaptation constraints in the case of scalable vide