467 research outputs found
Fast compressed domain watermarking of MPEG multiplexed streams
In this paper, a new technique for watermarking of
MPEG compressed video streams is proposed. The watermarking scheme operates directly in the domain of MPEG multiplexed streams. Perceptual models are used during the embedding process in order to preserve the quality of the video. The watermark is embedded in the compressed domain and is detected without the use of the original video sequence. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks. The resulting watermarking system is very fast and reliable, and is suitable for copyright protection and real-time content authentication applications
Fast watermarking of MPEG-1/2 streams using compressed-domain perceptual embedding and a generalized correlator detector
A novel technique is proposed for watermarking of MPEG-1 and MPEG-2 compressed video streams. The proposed scheme is applied directly in the domain of MPEG-1 system streams and MPEG-2 program streams (multiplexed streams). Perceptual models are used during the embedding process in order to avoid degradation of the video quality. The watermark is detected without the use of the original video sequence. A modified correlation-based detector is introduced that applies nonlinear preprocessing before correlation. Experimental evaluation demonstrates that the proposed scheme is able to withstand several common attacks. The resulting watermarking system is very fast and therefore suitable for copyright protection of compressed video
K-Space at TRECVid 2007
In this paper we describe K-Space participation in
TRECVid 2007. K-Space participated in two tasks, high-level feature extraction and interactive search. We present our approaches for each of these activities and provide a brief analysis of our results. Our high-level feature submission utilized multi-modal low-level features which included visual, audio and temporal elements. Specific concept detectors (such as Face detectors) developed by K-Space partners were also used. We experimented with different machine learning approaches including logistic regression and support vector machines (SVM). Finally we also experimented with both early and late fusion for feature combination. This year we also participated in interactive search, submitting 6 runs. We developed two interfaces which both utilized the same retrieval functionality. Our objective was to measure the effect of context, which was supported to different degrees in each interface, on user performance.
The first of the two systems was a ‘shot’ based interface,
where the results from a query were presented as a ranked
list of shots. The second interface was ‘broadcast’ based,
where results were presented as a ranked list of broadcasts.
Both systems made use of the outputs of our high-level feature submission as well as low-level visual features
Survey of image-based representations and compression techniques
In this paper, we survey the techniques for image-based rendering (IBR) and for compressing image-based representations. Unlike traditional three-dimensional (3-D) computer graphics, in which 3-D geometry of the scene is known, IBR techniques render novel views directly from input images. IBR techniques can be classified into three categories according to how much geometric information is used: rendering without geometry, rendering with implicit geometry (i.e., correspondence), and rendering with explicit geometry (either with approximate or accurate geometry). We discuss the characteristics of these categories and their representative techniques. IBR techniques demonstrate a surprising diverse range in their extent of use of images and geometry in representing 3-D scenes. We explore the issues in trading off the use of images and geometry by revisiting plenoptic-sampling analysis and the notions of view dependency and geometric proxies. Finally, we highlight compression techniques specifically designed for image-based representations. Such compression techniques are important in making IBR techniques practical.published_or_final_versio
MediaSync: Handbook on Multimedia Synchronization
This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences
Understanding user experience of mobile video: Framework, measurement, and optimization
Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study
Dynamic adaptation of streamed real-time E-learning videos over the internet
Even though the e-learning is becoming increasingly popular in the academic environment,
the quality of synchronous e-learning video is still substandard and significant work needs to be
done to improve it. The improvements have to be brought about taking into considerations both:
the network requirements and the psycho- physical aspects of the human visual system.
One of the problems of the synchronous e-learning video is that the head-and-shoulder video
of the instructor is mostly transmitted. This video presentation can be made more interesting by
transmitting shots from different angles and zooms. Unfortunately, the transmission of such
multi-shot videos will increase packet delay, jitter and other artifacts caused by frequent
changes of the scenes. To some extent these problems may be reduced by controlled reduction
of the quality of video so as to minimise uncontrolled corruption of the stream. Hence, there is a
need for controlled streaming of a multi-shot e-learning video in response to the changing
availability of the bandwidth, while utilising the available bandwidth to the maximum.
The quality of transmitted video can be improved by removing the redundant background
data and utilising the available bandwidth for sending high-resolution foreground information.
While a number of schemes exist to identify and remove the background from the foreground,
very few studies exist on the identification and separation of the two based on the understanding
of the human visual system. Research has been carried out to define foreground and background
in the context of e-learning video on the basis of human psychology. The results have been
utilised to propose methods for improving the transmission of e-learning videos.
In order to transmit the video sequence efficiently this research proposes the use of Feed-
Forward Controllers that dynamically characterise the ongoing scene and adjust the streaming
of video based on the availability of the bandwidth. In order to satisfy a number of receivers
connected by varied bandwidth links in a heterogeneous environment, the use of Multi-Layer
Feed-Forward Controller has been researched. This controller dynamically characterises the
complexity (number of Macroblocks per frame) of the ongoing video sequence and combines it
with the knowledge of availability of the bandwidth to various receivers to divide the video
sequence into layers in an optimal way before transmitting it into network.
The Single-layer Feed-Forward Controller inputs the complexity (Spatial Information and
Temporal Information) of the on-going video sequence along with the availability of bandwidth
to a receiver and adjusts the resolution and frame rate of individual scenes to transmit the
sequence optimised to give the most acceptable perceptual quality within the bandwidth
constraints.
The performance of the Feed-Forward Controllers have been evaluated under simulated
conditions and have been found to effectively regulate the streaming of real-time e-learning
videos in order to provide perceptually improved video quality within the constraints of the
available bandwidth
Streaming and User Behaviour in Omnidirectional Videos
Omnidirectional videos (ODVs) have gone beyond the passive paradigm of traditional video,
offering higher degrees of immersion and interaction. The revolutionary novelty of this technology is the possibility for users to interact with the surrounding environment, and to feel a
sense of engagement and presence in a virtual space. Users are clearly the main driving force of
immersive applications and consequentially the services need to be properly tailored to them.
In this context, this chapter highlights the importance of the new role of users in ODV streaming applications, and thus the need for understanding their behaviour while navigating within
ODVs. A comprehensive overview of the research efforts aimed at advancing ODV streaming
systems is also presented. In particular, the state-of-the-art solutions under examination in this
chapter are distinguished in terms of system-centric and user-centric streaming approaches: the
former approach comes from a quite straightforward extension of well-established solutions for
the 2D video pipeline while the latter one takes the benefit of understanding users’ behaviour
and enable more personalised ODV streaming
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