A high effort in Quality of Experience (QoE) research has been put into subjective assessment to determine the perceived quality of video. Most laboratory experiments follow guidelines from the ITU-T Recommendations, which suggest Absolute Category Rating (ACR) as a method to conduct such experiments. However, this method of video assessment radically limits confounding variables, is unnatural, and is far from how people cope with quality degradation and the cues they receive in these situations. This paper addresses this issue and proposes a more realistic subjective experiment based on the participant's behavior. Instead of passively rating the degraded quality of silent videos, we created the possibility to react to the annoying quality of chosen Netflix movies and reward participants by increasing the quality to the best possible. To cope with the data obtained, we adapted the method of fitting psychometric functions known in neuroscience, auditory science, animal science, and psychology. As a result, we obtained a more comprehensive image of the participants and their perceived quality, including their consistency, lapses, and differences. We estimated the parameters using Maximum Likelihood Estimation (MLE) and evaluated the goodness-of-fit of three S-shaped functions: Weibull, cumulative normal, and logistic. In the end, as the most common, we analyze the basic properties of the fitted functions, such as the Point of Subjective Equality (PSE), confidence intervals, and slope (β). We examine their role in describing individual differences among 34 subjects.

The key objective of No-Reference (NR) visual metrics (indicators) is to predict the end-user experience concerning remotely delivered video content. Rapidly increasing demand for easily accessible, high quality video material makes it crucial for service providers to test the user experience without the need for comparison with reference material. In this paper, we present a versatile measurement system and describe various optimisation strategies utilised to reach real-time operation. Furthermore, several calculation automation scripts are described, along with a dedicated graphical user interface, which gives a more comprehensive insight into the presented system. On top of that, we show the results of crowd-sourcing experiments used to estimate subjective threshold values for quality indicators. Additionally, integration with the IMCOP system is introduced.

Video streaming is growing exponentially. High-resolution videos require high bandwidth to transport the videos over the network. There is a great demand for compression technologies to compress video and maintain quality. Video codecs are used to encode and decode video streams. These codecs have been developed by MPEG, Google, Microsoft, and Apple Inc. The goal of this research is to develop a technology that will realize contribution transmission through connecting the latest methods generation of single and multi-way video encoding with the new protocols that will provide transmission reliability and keep low latency. A literature review will be carried out. The literature covers different video codecs and transmission techniques and the methods used to evaluate the quality of those techniques and codecs. Based on the literature review, the theoretical framework will be formed, and a video encoding method prototype will be developed. The developed method will be for one-way and multi-way software that will automatically optimize the settings of the video codec to set its operating conditions at optimal. The new transmission software will use newer codecs, such as H265/HEVC, VP9, and AV1, MPEG5, which will allow additional reduction of the bit stream and deliver secure, reliable, and quality video with low latency.

Recently an impressive development in immersive technologies, such as Augmented Reality (AR), Virtual Reality (VR) and 360${^\circ }$video, has been witnessed. However, methods for quality assessment have not been keeping up. This paper studies quality assessment of 360${^\circ }$video from the cross-lab tests (involving ten laboratories and more than 300 participants) carried out by the Immersive Media Group (IMG) of the Video Quality Experts Group (VQEG). These tests were addressed to assess and validate subjective evaluation methodologies for 360${^\circ }$video. Audiovisual quality, simulator sickness symptoms, and exploration behavior were evaluated with short (from 10 seconds to 30 seconds) 360${^\circ }$sequences. The following factors’ influences were also analyzed: assessment methodology, sequence duration, Head-Mounted Display (HMD) device, uniform and non-uniform coding degradations, and simulator sickness assessment methods. The obtained results have demonstrated the validity of Absolute Category Rating (ACR) and Degradation Category Rating (DCR) for subjective tests with 360${^\circ }$videos, the possibility of using 10-second videos (with or without audio) when addressing quality evaluation of coding artifacts, as well as any commercial HMD (satisfying minimum requirements). Also, more efficient methods than the long Simulator Sickness Questionnaire (SSQ) have been proposed to evaluate related symptoms with 360${^\circ }$videos. These results have been instrumental for the development of the ITU-T Recommendation P.919. Finally, the annotated dataset from the tests is made publicly available for the research community.

In this paper, we will present a study concerning the understanding of the needs of people using Internet in order to access to multilingual information. In fact, in the framework of AMIS (Accessing Multilingual Information and opinionS), a Chist-Era project, we propose to develop a system which will help to understand the main idea of a video in a foreign language. In order to design a useful system, a survey allowing to specify the profile of potential users of AMIS has been conducted. The study concerned 170 people from different countries: Poland, Spain and France. The sample is composed of people of different ages and different culture and languages.The results, in terms of requirements, achieved from this study show differences depending on how often the people watch the news on TV or review them on the Internet, and on the age of the target group. These concrete results help us in several decisions concerning how to build a realistic architecture of AMIS.

Over 10 billion hours of video are watched online every month. Together with high definition television broadcasting and the rise in high quality video on demand, this makes quality assessment a key task in the global multimedia market. Automating quality checking is currently based on finding major audiovisual artefacts. The Monitoring Of Audio Visual quality by key Indicators (MOAVI) subgroup of the Video Quality Experts Group (VQEG) is an open collaborative project for developing No-Reference models for monitoring audiovisual service quality. The purpose of this paper is to report on the development of the audiovisual part of this project, which includes the detection of muting, clipping and lip synchronization (also known as lip sync) artefacts.

The security of citizens constitutes an issue of primary importance. Constant improvements in security should be one of the strategic activities of any government and its agencies such as police, city police, firemen, local administration, etc.

In addition to traditional Quality of Service (QoS), Quality of Experience (QoE) poses a real challenge for Internet service providers, audio-visual services, broadcasters and new Over-The-Top (OTT) services. Therefore, objective audio-visual metrics are frequently being dedicated in order to monitor, troubleshoot, investigate and set benchmarks of content applications working in real-time or off-line. The concept proposed here, Monitoring of Audio Visual Quality by Key Performance Indicators (MOAVI), is able to isolate and focus investigation, set-up algorithms, increase the monitoring period and guarantee better prediction of perceptual quality. MOAVI artefacts Key Performance Indicators (KPI) are classified into four categories, based on their origin: capturing, processing, transmission, and display. In the paper, we present experiments carried out over several steps with four experimental set-ups for concept verification. The methodology takes into the account annoyance visibility threshold. The experimental methodology is adapted from International Telecommunication Union – Telecommunication Standardization Sector (ITU-T) Recommendations: P.800, P.910 and P.930. We also present the results of KPI verification tests. Finally, we also describe the first implementation of MOAVI KPI in a commercial product: the NET-MOZAIC probe. Net Research, LLC, currently offers the probe as a part of NET-xTVMS Internet Protocol Television (IPTV) and Cable Television (CATV) monitoring system.

A tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.

The contemporary world presents us with numerous dangers and challenges. We hear about traffic accidents, crimes, confrontations between football hooligans, building disasters, etc. on the news almost every day. In addition, terrorism has become a growing threat. In order to prevent and combat such hazards, new intelligent solutions are required. Traditional urban monitoring and surveillance systems, with operators overseeing any activities taking place, are no longer sufficient, mainly because of the petabytes of data per minute that need to be analyzed. Such a vast volume of data in current urban monitoring systems is the result of widespread and growing use of various sensors, mainly digital cameras and microphones. Therefore, new intelligent approaches for image and audio processing and recognition are vital for modern security systems; in turn, they would not be effective without innovative data encryption and protection techniques, including those relying on digital watermarking.

The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage time-frame, discrimination level, target size, lighting level, and level of motion. These parameters form what are referred to as Generalized Use Classes (GUCs). The aim of our research was to develop algorithms that would automatically assist classification of input sequences into one of the GUCs. Target size and lighting level parameters were approached. The experiment described reveals the experts' ambiguity and hesitation during the manual target size determination process. However, the automatic methods developed for target size classification make it possible to determine GUC parameters with 70 % compliance to the end-users' opinion. Lighting levels of the entire sequence can be classified with an efficiency reaching 93 %. To make the algorithms available for use, a test application has been developed. It is able to process video files and display classification results, the user interface being very simple and requiring only minimal user interaction.

Multimedia, Communications, Services and Security" has been an important research topic in recent years and a key part of innovative ICT projects.In particular, numerous intelligent systems benefit from the integration of tools and solutions proposed by scientists, such as image, video and audio processing, development of intelligent sensors, interlinking heterogeneous subsystems with intra-and internet services, and providing reliable and secure communications channels.This special issue consists of eleven papers, which are briefly discussed as follows.In "Detection and Localization of Selected Acoustic Events in Acoustic Fields for Smart Surveillance Applications," the authors provide a method for determining the position of selected sound events in 3D space.When an event is detected (e.g.speech or impulse sound), the sound source is located so that it can be used in surveillance systems.The following two papers are related to Quality of Experience issues."Quality Assessment of Visual and Automatic Licence Plate Recognition" discusses the Quality of Experience in Automatic Licence Plate Recognition tasks based on surveillance videos streamed under constrained networking conditions.Based on the presented assumptions, the authors implement automatic recognition algorithms and compare their accuracy against user perception in order to obtain quality models and critical quality thresholds."A Journey from Subjective Psychophysical Experiments to Objective Quality Optimisation" presents two task-based video experiments in surveillance and medical applications.The problem of quality assessment, from subjective psychophysical experiments to objective quality models, is discussed.Example test results and models are provided.

Development of techniques for assessing video quality is reviewed. Examples have been provided on the quality of video applications ranging from popular entertainment to new trends such as applications in wide-reaching public systems, not just those used by security forces but also for medical purposes. In particular, two typical usages of task-based video: surveillance video for accurate licence plate recognition, and medical video for credible diagnosis prior to bronchoscopic surgery were introduced by the author. The problem of task-based video quality assessment starting from subjective psychophysiological experiments to objective quality models is discussed. Example test results and models are provided alongside to the descriptions. Finally, a quality optimisation approach, driven by recognition rates is presented.

Intelligent monitoring is currently one of the most prominent research areas. Numerous aspects of such schemes need to be addressed by implementation of various modules covering a wide range of algorithms, beginning from video analytic modules, through quality assessment, up to integrity verification. The goal of this paper is to provide a brief overview of the most recent research results regarding various aspects of the video surveillance processing chain. Specifically, the paper describes a scheme for automatic recognition of the make and model of passing vehicles, the state-of-the-art in quality assessment for recognition tasks, and a system for verification of digital evidence integrity. Concluding remarks highlight the perspectives for further development of the described techniques, and the related research directions.

The paper proposes a No-Reference (NR) metric to objectively assess the H.264/AVC video quality. The proposed model takes into account the typical artefacts introduced by hybrid block-based motion compensated predictive video codecs as the one related to the H.264/AVC standard. More specifically, these artefacts are the blockiness introduced at the boundaries of each coded block and the temporal flickering due to different coding modes used for the same macroblock along the video sequence. Furthermore, a flickering metric for intra coded frames is also derived. The quality prediction accuracy of the proposed NR quality metric is validated over subjective data collected during a video subjective evaluation experiments. Moreover, the quality prediction accuracy is also compared with the one provided by the well known state-of-the-art Structural SIMilarity (SSIM) metric which works in a full-reference mode. The proposed metric achieves a higher Pearson's correlation coefficient with subjective scores than the one achieved by the SSIM metric.

In recent years, the ubiquity of multimedia services along with the proliferation of mobile devices and the demand for new audio and video applications are changing the lifestyle of users.The multimedia era is allowing users to create, distribute, and access content in ubiquitous way and cost-effectively, while providers explore new ways to increase their revenues.The efficient delivery of real-time multimedia services over emerging diverse and heterogeneous systems is a challenging research goal.The interoperability of applications, transport and network protocols as well as the demand for improved Quality of Experience (QoE) create new challenges and opportunities for further research on novel communication protocols, architectures, and methods to efficiently support current and future multimedia networking systems.In 2010, the Third International Future Multimedia Networking (FMN 2010) workshop was organized in Kraków, Poland and achieved a success attracting numerous submissions from various countries.FMN 2010 produced a high quality peer reviewed technical programme with an acceptance rate at around 24% and addressed important aspects of future multimedia systems with a focus on QoE.Authors of selected papers from FMN 2010 were invited to submit extended versions of their papers in order to be considered for inclusion in this Special issue on Future Multimedia.

In the field of still and moving pictures digital imaging one of the most important factors affecting the quality of the acquisition is a correct exposure. This factor is especially important for video surveillance. It is particularly applicable in the case of CCTV cameras often operating in low-light conditions or blinded by an external light source. It is quite common that the lighting conditions are well below the adaptive capacity of a camera. Therefore, it is necessary to continuously monitor the level of exposure to determine image quality. It should be noted that the level of exposure is not expressed using quantitative parameters of acquisition (being sometimes meaningless from the perceived quality assessment point of view) but is measured directly on the image. The purpose of the presented research was to develop a No Reference (NR) metric assessing video Quality of Experience (QoE) affected with the exposure distortion. It was presumed that both over- and under-exposure degrade QoE, so the research task was to derive a proper mapping function between QoE and exposure. The presented exposure metric is unique and no similar research was found in the literature.

In recent years, the ubiquity of multimedia services along with the proliferation of mobile devices and the demand for new audio and video applications are changing the life style of users.The multimedia era is allowing users to create, distribute, and access content in ubiquitous way and cost-effectively, while providers explore new ways to increase their revenues.The efficient delivery of real-time multimedia services over emerging diverse and heterogeneous systems is a challenging research goal.The interoperability of applications, transport and network protocols as well as the demand for improved Quality of Service (QoS), Quality of Experience (QoE), and seamless mobility create new challenges and opportunities for further research on novel communication protocols, architectures, and methods to efficiently support current and future multimedia networking systems.In 2009, the Second International Future Multimedia Networking (FMN 2009) workshop was organized in Coimbra, Portugal and achieved exceptional success attracting 64 submissions from 33 countries.FMN 2009 produced a high quality peer reviewed technical programme with an acceptance rate at around 25% and addressed important aspects of future multimedia systems with a focus on Autonomic Content Networks.Authors of selected papers from FMN 2009 were invited to submit extended versions of their papers in order to be considered for inclusion in this Special issue on Future Multimedia.These papers were peer-reviewed again and then further revised by the authors.

In recent years, the ubiquity of multimedia services along with the proliferation of mobile devices and the demand for new audio and video applications are changing the life style of users. User demands for multimedia access anywhere, anytime from any device are creating new challenges for research communities from both academia and industry. It is expected that video-based services alone will account for 50 percent of all consumer network traffic in 2012 and we will continue to witness the explosive growth in users sharing multimedia content over the Internet. In this context, new network, application, and user-based approaches must be created to deal with such complex multimedia systems. This paper presents some of the recent advances in multimedia networking focusing primarily on areas that have been receiving attention recently and are expected to continue to generate further interests in coming years. These areas include Quality of Experience (QoE) and various related standardization issues, Content Distribution Networks (CDNs), multimedia communications, mobile Multimedia. This paper also briefly highlights some of the major challenges that still need to be addressed to enable the support and delivery of multimedia services anywhere, anytime over highly heterogeneous infrastructures and user terminal devices.