Search

This work concerns the study of the structural, energetic, and dynamic properties of fluorescent systems composed of silver clusters stabilized by polynucleotide strands. To do so, classical interaction potentials relative to silver, neutral and cationic, were introduced in the AMBER force field. Molecular dynamics simulations allowed analysis of the nature and force of the interactions between the various parts of the nucleic oligomers and the silver clusters. Conformational analyses were necessary to explore the flexibility of the supramolecular assemblies, specifically by radial distribution functions and Ramachandrantype maps.

HTTP adaptive streaming facilitates video streaming to mobile devices connected through heterogeneous networks without the need for a dedicated streaming infrastructure. By splitting different encoded versions of the same video into small segments, clients can contin- uously decide which segments to download based on available network resources and device characteristics. These encoded versions can, for example, differ in terms of bitrate and spatial or temporal resolution. However, as a result of dynamically selecting video segments, perceived video quality can fluctuate during playback which will impact end-users' quality of experience. Subjective studies have already been conducted to assess the influence of video delivery using HTTP Adaptive Streaming to mobile devices. Nevertheless, existing studies are limited to the evalu- ation of short video sequences in controlled environments. Research has already shown that video duration and assessment environment influence quality perception. Therefore, in this article, we go beyond the traditional ways for subjective quality evaluation by conducting novel experiments on tablet devices in more ecologically valid testing environments using longer duration video sequences. As such, we want to mimic realistic viewing behavior as much as possible. Our results show that both video content and the range of quality switches significantly influence end-users' rating behavior. In general, quality level switches are only perceived in high motion sequences or in case switching occurs between high and low quality video segments. Moreover, we also found that video stallings should be avoided during playback at all times.

Experimental data about 3D arrangements and building modes of cyclodextrin (CD) tubes are scarce, though investigations of such assemblies are particularly interesting for a vast array of applications related to organic tubes in general. Opting for a theoretical approach, we studied the organisation of CD tubes by three schemes: a structural examination of geometries from the Cambridge Structural Database, simulated annealing studies based on classical force fields to evaluate the stability of tubular arrangements, and an incremental construction procedure of the tubes by molecular dynamics. For β-CDs, the investigations pointed to a head-to-head configuration, while γ-CDs favoured a head-to-head+tail-to-head triplet. The position and interactions of water molecules inside the obtained tubular arrangements were studied as well. Various complexes for diphenylpolyenes and styrene included in the β- and γ-CDs tubes were considered and compared based on structural, energetic and dynamic criteria.

In order to ensure optimal quality of experience toward end users during video streaming, automatic video quality assessment becomes an important field-of-interest to video service providers. Objective video quality metrics try to estimate perceived quality with high accuracy and in an automated manner. In traditional approaches, these metrics model the complex properties of the human visual system. More recently, however, it has been shown that machine learning approaches can also yield competitive results. In this paper, we present a novel no-reference bitstream-based objective video quality metric that is constructed by genetic programming-based symbolic regression. A key benefit of this approach is that it calculates reliable white-box models that allow us to determine the importance of the parameters. Additionally, these models can provide human insight into the underlying principles of subjective video quality assessment. Numerical results show that perceived quality can be modeled with high accuracy using only parameters extracted from the received video bitstream.

The widespread availability of cloud infrastructures is fueling new interest in the thin client computing paradigm. However, current thin client protocols are not designed to handle new content types as often encountered in state-of-the-art applications (e.g. multimedia editing, gaming, multimedia playback). Conveying this content using traditional thin client protocols typically results in a combination of excessive resource usage and low visual quality. In this paper, we propose an approach where the content type can vary for different portions of the screen (e.g. combination of static text and video). Once the different content types have been detected, each of them can be encoded using the most appropriate algorithm. We present two algorithms for this runtime detection. The first algorithm is operating at the pixel level, thereby being independent of the actual thin client protocol used. The second algorithm assumes the presence of a rectangle-based thin client protocol (such as the popular VNC protocol), trading independence for improved performance. The appropriate parameter settings for these algorithms are experimentally determined. Furthermore, their influence is studied in detail in terms of detection accuracy, and the time to perform the algorithms is analysed. Accurate hints are derived within less than 10ms, indicating the high potential of this approach for use in next generation thin client systems.

The Digital Video Broadcast-Handheld (DVB-H) is an international standard which offers broadcast data services to mobile handheld devices. Its main enhancements to conventional Digital Video Broadcast-Terrestrial (DVB-T) systems include the addition of time-slicing and an extra stage of error correction, referred to as Multi-Protocol Encapsulation-Forward Error Correction (MPE-FEC) at the link layer. The essential components required to deploy an IP-based mobile TV service on top of DVB-H are described by the DVB standard for IP DataCast specifications (DVB-IPDC). Since mobile TV services mostly consist of real-time video data, very stringent demands in terms of quality of service (QoS) are imposed to the broadcast operator's primary distribution network. In this article, the impact of packet loss, introduced in a IP-based distribution network, on the quality of experience (QoE), the video quality as perceived by the end user, is characterised. In recent work, a first analysis of the impact of random packet loss was reported upon. This paper describes a more profound analysis of both random and burst packet loss by taking into account several objective video quality metrics. It is shown that, although MPE-FEC is introduced for better reception between antenna and receiver, its use has a major impact on the effects of packet loss in the distribution network. The use of error-correction techniques in the distribution network only has a beneficial impact on the QoE when lower MPE-FEC code rates are used. Moreover, the impact of action scenes or scene switches on the perceived video quality is also characterised in detail. Based on the experimental results, an analytical model is presented which allows to predict the QoE detoriation as a function of the burst loss probability in the distribution network.

User satisfaction is a key factor in the success of novel multimedia services. Yet, to enable service providers and network operators to control and maximize the quality (QoS, QoE) of delivered video streams, quite some challenges remain. In this paper, we particularly focus on three of them. First of all, objectively measuring video quality requires appropriate quality metrics and methods of assessing them in a real-time fashion. Secondly, the recent Scalable Video Coding (SVC) format opens opportunities for adapting video to the available (network) resources, yet the appropriate configuration of video encoding as well as real-time streaming adaptation are largely unaddressed research areas. Thirdly, while bandwidth reservation mechanisms in access/core networks do exist, service providers lack a means for guaranteeing QoS in the increasingly complex home networks (which they are not in full control of). In this paper we offer a broad view on these interrelated issues, by presenting the developments originating in a Flemish research project (including proof-of-concept demonstrations). From a developmental perspective, we propose an architecture combining a real-time video quality monitoring platform, on-the-fly adaptation (optimizing the video quality) and QoS reservation in a heterogeneous home network based on UPnP QoS v3. From a research perspective, we propose a new subjective test procedure that revealed user preference for temporal scalability over quality scalability. In addition, an extensive study on optimizing HD SVC encoding in IPTV scenarios with fluctuating bandwidth showed that under certain bandwidth constraints (prohibiting sufficient fidelity) spatial scalability is a better option than quality scalability.

International audience; The current development of video quality assessment algorithms suffers from the lack of available video sequences for training, verification and validation to determine and enhance the algorithm's application scope. The Joint Effort Group of the Video Quality Experts Group (VQEG-JEG) is currently driving efforts towards the creation of large scale, reproducible, and easy to use databases. These databases will contain bitstreams of recent video encoders (H.264, H.265), packet loss impairment patterns and impaired bitstreams, pre-parsed bitstream information into files in XML syntax, and well-known objective video quality measurement outputs. The database is continuously updated and enlarged using reproducible processing chains. Currently, more than 70,000 sequences are available for statistical analysis of video quality measurement algorithms. New research questions are posed as the database is designed to verify and validate models on a very large scale, testing and validating various scopes of applications, while subjective assessment has to be limited to a comparably small subset of the database. Special focus is given on the principles guiding the database development, and some results are given to illustrate the practical usefulness of such a database with respect to the detailed new research questions. key words: video quality assessment, large scale database, reproducible research

As part of assessing (audio)visual quality by means of subjective experiments, specific instructions are provided on how to evaluate and rate the different video sequences. Also, a training session is used to familiarize the observers with the experiment and the type (and range) of impairments they can expect. As such, observers 'know' what to look for and what to expect. However, what about the influence of context and user expectations on quality perception?

This study investigates to what extent subjects are influenced by second screen (2nd screen) usage in terms of perceiving and evaluating video quality impairments in an adaptive streaming scenario. A controlled between subjects test was set up to ascertain whether subjects that are using a related 2nd screen are less sensitive to video quality impairments compared to subjects not using a 2nd screen. Our results show a significant influence of 2nd screen usage in terms of impairment detection and evaluation. However, tests to measure whether this was attributable to a divided attention showed no effect.

HTTP adaptive streaming technology has become widely spread in multimedia services because of its ability to provide adaptation to characteristics of various viewing devices and dynamic network conditions. There are various studies targeting the optimization of adaptation strategy. However, in order to provide an optimal viewing experience to the end-user, it is crucial to get knowledge about the Quality of Experience (QoE) of different adaptation schemes. This paper overviews the state of the art concerning subjective evaluation of adaptive streaming QoE and highlights the challenges and open research questions related to QoE assessment.

International audience; Several factors limit the advances on automatizing video quality measurement. Modelling the human visual system requires multi- and interdisciplinary efforts. A joint effort may bridge the large gap between the knowledge required in conducting a psychophysical experiment on isolated visual stimuli to engineering a universal model for video quality estimation under real-time constraints. The verification and validation requires input reaching from professional content production to innovative machine learning algorithms. Our paper aims at highlighting the complex interactions and the multitude of open questions as well as industrial requirements that led to the creation of the Joint Effort Group in the Video Quality Experts Group. The paper will zoom in on the first activity, the creation of a hybrid video quality model.

With the advent of cloud computing and remote execution of interactive applications, there is a need for evaluating the Quality of Experience (QoE) and the influence on this QoE of network condition variations, media encoding parameter settings and related optimization algorithms. However, current QoE assessment focuses mainly on audiovisual quality in non-interactive applications, such as video-on-demand services. On the other hand, where experiments aim to quantify interactive quality, the focus is typically targeted at games, using an ad-hoc test setup to assess the impact of network variations on the playing experience. In this paper, we present a novel platform enabling the assessment of a broad range of interactive applications (e.g., thin client remote desktop systems, remotely rendered engineering applications, games). Dynamic reconfiguration of media encoding and decoding is built into the system, to allow dynamic adaptation of the media encoding to the network conditions and the application characteristics. Evaluating the influence of these automatic adaptations is a key asset of our approach. A range of possible use cases is discussed, as well as a performance study of our implementation, showing that the platform we built is capable of highly controllable subjective user assessment. Furthermore, we present results obtained by applying the platform for a subjective evaluation of an interactive multimedia application. Specifically, the influence of visual quality and frame rate on interactive QoE has been assessed for a remotely executed race game.

Video distribution over error-prone Internet Protocol (IP) networks results in visual impairments on the received video streams. Objective impairment detection algorithms are crucial for maintaining a high Quality of Experience (QoE) as provided with IPTV distribution. There is a lot of research invested in H.264/AVC impairment detection models and questions rise if these turn obsolete with a transition to the successor of H.264/AVC, called High Efficiency Video Coding (HEVC). In this paper, first we show that impairments on HEVC compressed sequences are more visible compaired to H.264/AVC encoded sequences. We also show that an impairment detection model designed for H.264/AVC could be reused on HEVC, but that caution is advised. A more accurate model taking into account content classification needed slight modification to remain applicable for HEVC compression video content.

Lip synchronization is considered a key parameter during interactive communication. In the case of video conferencing and television broadcasting, the differential delay between audio and video should remain below certain thresholds, as recommended by several standardization bodies. However, further research has also shown that these thresholds can be relaxed, depending on the targeted application and use case. In this article, we investigate the influence of lip sync on the ability to perform real-time language interpretation during video conferencing. Furthermore, we are also interested in determining proper lip sync visibility thresholds applicable to this use case. Therefore, we conducted a subjective experiment using expert interpreters, which were required to perform a simultaneous translation, and non-experts. Our results show that significant differences are obtained when conducting subjective experiments with expert interpreters. As interpreters are primarily focused on performing the simultaneous translation, lip sync detectability thresholds are higher compared with existing recommended thresholds. As such, primary focus and the targeted application and use case are important factors to be considered when selecting proper lip sync acceptability thresholds.

Thanks to the availability of 3D-capable televisions and bluray players, 3D content is made accessible in the home. Recently, an extension of the H.264/AVC video coding standard has been defined for encoding 3D video content. This extension, called Multiview Video Coding, allows inter-view prediction resulting in a better compression efficiency. However, due to these inter-view dependencies impairments in one view caused by e.g. packet losses can lead to degradations in other views. Research has already been conducted towards estimating packet loss visibility in H.264/AVC encoded sequences. In this paper, we investigate the possibility of using an existing decision tree-based classifier for estimating impairment visibility in 3D MVC encoded sequences. Our results show that, in the case of losing entire pictures, it is possible to estimate packet loss visibility in 3D MVC encoded sequences with a high accuracy by only taking into account a limited number of parameters.

This paper presents research on willingness to pay for audiovisual quality enhancements

Ensuring and maintaining adequate Quality of Experience towards end-users are key objectives for video service providers, not only for increasing customer satisfaction but also as service differentiator. However, in the case of High Definition video streaming over IP-based networks, network impairments such as packet loss can severely degrade the perceived visual quality. Several standard organizations have established a minimum set of performance objectives which should be achieved for obtaining satisfactory quality. Therefore, video service providers should continuously monitor the network and the quality of the received video streams in order to detect visual degradations. Objective video quality metrics enable automatic measurement of perceived quality. Unfortunately, the most reliable metrics require access to both the original and the received video streams which makes them inappropriate for real-time monitoring. In this article, we present a novel no-reference bitstream-based visual quality impairment detector which enables real-time detection of visual degradations caused by network impairments. By only incorporating information extracted from the encoded bitstream, network impairments are classified as visible or invisible to the end-user. Our results show that impairment visibility can be classified with a high accuracy which enables real-time validation of the existing performance objectives.

Subjective video quality experiments are usually conducted inside controlled lab environments, where stringent demands are imposed in terms of lighting conditions, screen calibration and position of the test subjects. However, these controlled lab environments might differ from a more natural setting such as watching television at home. This, in turn, will influence subjects' Quality of Experience. In previous research, we conducted a series of subjective experiments, mimicking the natural environment of the targeted use cases as much as possible. In this paper, we provide an overview of these conducted studies and summarize our main research findings. Our results show that the environment and overall experimental setup influence the primary focus of the test subjects. Consequently, a significant difference in impairment visibility, tolerance and annoyance is observed compared to conducting experiments in pristine lab environments. Our results highlight the importance of considering the targeted use case and assessing video quality in more natural environments.

Since 1997, the Video Quality Experts Group (VQEG) has been active in the field of subjective and objective video quality assessment. The group has validated competitive quality metrics throughout several projects. Each of these projects requires mandatory actions such as creating a testplan and obtaining databases consisting of degraded video sequences with corresponding subjective quality ratings. Recently, VQEG started a new open initiative, the Joint Effort Group (JEG), for encouraging joint collaboration on all mandatory actions needed to validate video quality metrics. Within the JEG, effort is made to advance the field of both subjective and objective video quality measurement by providing proper software tools and subjective databases to the community. One of the subprojects of the JEG is the joint development of a hybrid H.264/AVC objective quality metric. In this paper, we introduce the JEG and provide an overview of the different ongoing activities within this newly started group.

In order to ensure adequate quality towards the end users at all time, video service providers are getting more interested in monitoring their video streams. Objective video quality metrics provide a means of measuring (audio)visual quality in an automated manner. Unfortunately, most of the current existing metrics cannot be used for real-time monitoring due to their dependencies on the original video sequence. In this paper we present a new objective video quality metric which classifies packet loss as visible or invisible based on information extracted solely from the captured encoded H.264/AVC video bit stream. Our results show that the visibility of packet loss can be predicted with a high accuracy, without the need for deep packet inspection. This enables service providers to monitor quality in real-time.

The ever growing bandwidth in access networks, in combination with IPTV and video on demand (VoD) offerings, opens up unlimited possibilities to the users. The operators can no longer compete solely on the number of channels or content and increasingly make high definition channels and quality of experience (QoE) a service differentiator. Currently, the most reliable way of assessing and measuring QoE is conducting subjective experiments, where human observers evaluate a series of short video sequences, using one of the international standardized subjective quality assessment methodologies. Unfortunately, since these subjective experiments need to be conducted in controlled environments and pose limitations on the sequences and overall experiment duration they cannot be used for real-life QoE assessment of IPTV and VoD services. In this article, we propose a novel subjective quality assessment methodology based on full-length movies. Our methodology enables audiovisual quality assessment in the same environments and under the same conditions users typically watch television. Using our new methodology we conducted subjective experiments and compared the outcome with the results from a subjective test conducted using a standardized method. Our findings indicate significant differences in terms of impairment visibility and tolerance and highlight the importance of real-life QoE assessment.

Real-time Quality of Experience monitoring be- comes an important field-of-interest for video service providers. Early detection of impairments caused by, for example, packet loss in the IP-based delivery network enables service providers to take the necessary actions in order to maximize end-users' perception of quality. The influence of network impairments on visual quality depends on characteristics of the video stream such as the amount of motion and spatial detail. Therefore, streams should be monitored and parsed beyond the network layer. In this paper, we present a distributed video stream monitoring architecture and evaluate the real-time capability of parsing video streams up to the video layer. Our results indicate that it is possible to process a single video stream up to 60Mbit/s using commodity hardware when monitoring network parameters and high level video parameters such as frame type. A higher total bitrate can be achieved when monitoring multiple video streams encoded at lower bitrates. However, when detailed video parameters such as motion vectors and residual coefficients must be gathered, specialized hardware is needed. I. INTRODUCTION In recent years video applications like video conferencing and live video streaming have gained interest and it is expected that their importance in IP networks will continue to grow. Due to the real-time character of these applications a connectionless transport protocol like UDP is typically used. Hence problems within the network can result in packet loss and late arrival of packets causing a degradation in quality of the received video stream. For video service providers it is a challenge to ensure that their service provides the minimum quality expected by the users. To ensure end-to-end quality a proactive approach is desired, by monitoring video streams at strategic demarcation points along the delivery chain, problems within the network can be detected. Measuring Quality of Experience combined with the measurement of network statistics allows operators to link quality losses to the causes at the network level. This paper describes an architecture to monitor video streams in IP networks in a distributed way. We also answer the question whether it is possible to measure network statis- tics and video application layer data for a full High Definition 1 video stream in real-time with commodity hardware. The paper is organized as follows. In section two we describe some related work in the area of video monitoring in IP networks. Section three discusses the general monitoring architecture and goes into more detail on how packets are captured and processed in the network probe. The fourth