Mikołaj Leszczuk

Framework for the integrated video quality assessment

Through years of development Content Networks (CN) have become more sophisticated and more technically diverse. Modern CN are designed to be more adaptive to communication environment, devices and user requirements. However, one open issue is the still fluctuating quality of service provision. As a result user experience can be negatively affected. In order to maintain a satisfactory level of user experience it is crucial to develop a feasible solution to measure the extent to which video services meet users’ expectation. Assessing video quality with respect to users’ subjective opinions is a complex task. In this paper we address challenges of this task and design an integrated framework using a number of comprehensive functional modules. Our framework integrates objective quality assessment models of Artifacts Measurement (AM) and Quality of Delivery (QoD) approaches. Only the fittest models are activated by the framework considering requirements of individual evaluation tasks. We also introduce our recent work of realising key functional modules of the framework. Joint subjective experiments between two institutes have also been carried out for the purpose of model implementation and evaluation. Results from experiments verify the concept of an integrated framework and show the effectiveness of its key modules in estimating the quality level of video services.

Perceptual quality assessment for H.264/AVC compression

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 Pearsons correlation coefficient with subjective scores than the one achieved by the SSIM metric.

Recent advances in multimedia networking

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.

Quality Assessment for a Licence Plate Recognition Task Based on a Video Streamed in Limited Networking Conditions

Video transmission and analysis is often utilised in applications outside of the entertainment sector, and generally speaking this class of video is used to perform a specific task. Examples of these applications are security and public safety. The Quality of Experience (QoE) concept for video content used for entertainment differs significantly from the QoE of surveillance video used for recognition tasks. This is because, in the latter case, the subjective satisfaction of the user depends on achieving a given functionality. Moreover, such sequences have to be compressed significantly because the monitored place has to be seen on-line and it can be connected by an error prone wireless connection. Recognising the growing importance of video in delivering a range of public safety services, we focused on developing critical quality thresholds in licence plate recognition tasks based on videos streamed in constrained networking conditions.

Future Multimedia Networking

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Recent developments in visual quality monitoring by key performance indicators

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.

Determining image quality requirements for recognition tasks in generalized public safety video applications: Definitions, testing, standardization, and current trends

Currently, even though the Quality of Experience (QoE) concept for video content used for entertainment differs materially from the QoE of video used for public safety tasks (because in the latter case, the subjective satisfaction of the user depends upon achieving the given task), there are nearly no quality standards for these video applications. This is an important problem as the transmission and analysis of video is often used for many applications outside of the entertainment sector, and generally this class of video is used to perform a specific task. Therefore, in this paper, we introduce new methods of assessing video quality for task-based video that have been under development. Once a framework and measurement system have been developed for task-based video, performance specifications and standards can be developed to assist users of task-based video in determining the technology that is going to successfully allow them to perform the function required.

Automated qualitative assessment of multi-modal distortions in digital images based on GLZ

This paper introduces a novel approach to a qualitative assessment of images affected by multi-modal distortions. The idea is to assess the image quality perceived by an end user in an automatic way in order to avoid the usual time-consuming, costly and non-repeatable method of collecting subjective scores during a psycho-physical experiment. This is achieved by computing quantitative image distortions and mapping results on qualitative scores. Useful mapping models have been proposed and constructed using the generalised linear model (GLZ), which is a generalisation of the least squares regression in statistics for ordinal data. Overall qualitative image distortion is computed based on partial quantitative distortions from component algorithms operating on specified image features. Seven such algorithms are applied to successfully analyse the seven image distortions in relation to the original image. A survey of over 12,000 subjective quality scores has been carried out in order to determine the influence of these features on the perceived image quality. The results of quantitative assessments are mapped on the surveyed scores to obtain an overall quality score of the image. The proposed models have been validated in order to prove that the above technique can be applied to automatic image quality assessment.

Automated Detection of Firearms and Knives in a CCTV Image

Closed circuit television systems (CCTV) are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by human factors. In this paper, we focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims.

Assessing Task-Based Video Quality — A Journey from Subjective Psycho-Physical Experiments to Objective Quality Models

This paper reviews the development of techniques for assessing video quality. Examples have been provided on the quality of video applications ranging from popular entertainment to new trends such as applications in broad public systems, not just those used by police forces but also for medical purposes. In particular, the author introduces two typical usages of task-based video: surveillance video for accurate licence plate recognition, and medical video for credible diagnosis prior to bronchoscopic surgery. The author also presents the field of task-based video quality assessment from subjective psycho-physical experiments to objective quality models. Example test results and models are provided alongside the descriptions.