166 research outputs found

    Video streaming

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    Measuring quality of video of internet protocol television (IPTV)

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    141 p.La motivación para el desarrollo de esta tesis es la necesidad que existe de monitorizar la calidad de experiencia del vídeo que se proporciona en una red IPTV (Internet Protocol Television). Esta necesidad surge del deseo de los operadores de telecomunicaciones de proporcionar un servicio más satisfactorio a sus clientes y alcanzar mayor penetración en el mercado. Los servicios sólo pueden tener éxito si la calidad de experiencia se garantiza. Las redes IPTV (Television sobre IP) son por naturaleza susceptibles a pérdidas de paquetes de datos que afectan a la calidad del vídeo que recibe el usuario. Entre los factores que contribuyen a la existencia de pérdida de paquetes de datos se encuentran la congestión de red, una planificación de red inadecuada o el fallo de algún equipamiento de la red. La calidad de experiencia de un vídeo se ve afectada por una serie de factores como por ejemplo la resolución, la ausencia de errores en las imágenes, la calidad de la televisión, las expectativas previas del usuario y muchos otros factores que se estudian en esta tesis

    Measuring quality of video of internet protocol television (IPTV)

    Get PDF
    141 p.La motivación para el desarrollo de esta tesis es la necesidad que existe de monitorizar la calidad de experiencia del vídeo que se proporciona en una red IPTV (Internet Protocol Television). Esta necesidad surge del deseo de los operadores de telecomunicaciones de proporcionar un servicio más satisfactorio a sus clientes y alcanzar mayor penetración en el mercado. Los servicios sólo pueden tener éxito si la calidad de experiencia se garantiza. Las redes IPTV (Television sobre IP) son por naturaleza susceptibles a pérdidas de paquetes de datos que afectan a la calidad del vídeo que recibe el usuario. Entre los factores que contribuyen a la existencia de pérdida de paquetes de datos se encuentran la congestión de red, una planificación de red inadecuada o el fallo de algún equipamiento de la red. La calidad de experiencia de un vídeo se ve afectada por una serie de factores como por ejemplo la resolución, la ausencia de errores en las imágenes, la calidad de la televisión, las expectativas previas del usuario y muchos otros factores que se estudian en esta tesis

    Routine tests for both planning and evaluating image quality in tele-echocardiography

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    Both in real-time and "store & forward" tele-echocardiography (T-E), a coding process has to be applied to the echocardiography videoclips in order to limit the bandwidth needed and adapt it to the bandwidths furnished by network providers. The compression process degrades the videoclips, affecting thus the quality of the videoclips and potentially compromising the diagnostic accuracy of the T-E. In this work the authors investigated on the use of automatic tools for the video quality assessment by means of objective methods with particular care to the role of the system administrator. As the use of tests on video quality assessment (based on subjective methods) is hampered by the high number of needed resources (persons, laboratories and time). The use of valid objective methods is thus desirable. The study reviewed different tools with this specific aim. One of the more suitable tool was found to be represented by a software package designed by the Institute of Telecommunication Sciences and the National Telecommunication and Information Administration, the NTIA/ITS VQM tool. This tool gives back objective-quantitative data as outcomes, however embeds models emulating the subjective perception. This study reviewed and analyzed in depth the functionalities of the tool to improve the image quality in TE over the network. The tool was also found suitable for a more general process of T-E assessment, from a health technology assessment (HTA) perspective

    A reduced-reference perceptual image and video quality metric based on edge preservation

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    In image and video compression and transmission, it is important to rely on an objective image/video quality metric which accurately represents the subjective quality of processed images and video sequences. In some scenarios, it is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one. For instance, for quality improvement of video transmission through closed-loop optimisation, the video quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image/video sequence-prior to compression and transmission-is not usually available at the receiver side, and it is important to rely at the receiver side on an objective video quality metric that does not need reference or needs minimal reference to the original video sequence. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric. © 2012 Martini et al

    Computational inference and control of quality in multimedia services

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    Quality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered delity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that aect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relationships. The subjectively perceived QoE is hard to measure directly and continuously evolves with the user's expectations. Faced with the diculty of designing an expert system for QoE management that relies on painstaking measurements and intricate heuristics, we turn to an approach based on learning or inference. The set of solutions presented in this work rely on computational intelligence techniques that do inference over the large set of signals coming from the system to deliver QoE models based on user feedback. We furthermore present solutions for inference of optimized control in systems with no guarantees for resource availability. This approach oers the opportunity to be more accurate in assessing the perceived quality, to incorporate more factors and to adapt as technology and user expectations evolve. In a similar fashion, the inferred control strategies can uncover more intricate patterns coming from the sensors and therefore implement farther-reaching decisions. Similarly to natural systems, this continuous adaptation and learning makes these systems more robust to perturbations in the environment, longer lasting accuracy and higher eciency in dealing with increased complexity. Overcoming this increasing complexity and diversity is crucial for addressing the challenges of future multimedia system. Through experiments and simulations this work demonstrates that adopting an approach of learning can improve the sub jective and objective QoE estimation, enable the implementation of ecient and scalable QoE management as well as ecient control mechanisms

    A QoE adaptive management system for high definition video streaming over wireless networks

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    [EN] The development of the smart devices had led to demanding high-quality streaming videos over wireless communications. In Multimedia technology, the Ultra-High Definition (UHD) video quality has an important role due to the smart devices that are capable of capturing and processing high-quality video content. Since delivery of the high-quality video stream over the wireless networks adds challenges to the end-users, the network behaviors 'factors such as delay of arriving packets, delay variation between packets, and packet loss, are impacted on the Quality of Experience (QoE). Moreover, the characteristics of the video and the devices are other impacts, which influenced by the QoE. In this research work, the influence of the involved parameters is studied based on characteristics of the video, wireless channel capacity, and receivers' aspects, which collapse the QoE. Then, the impact of the aforementioned parameters on both subjective and objective QoE is studied. A smart algorithm for video stream services is proposed to optimize assessing and managing the QoE of clients (end-users). The proposed algorithm includes two approaches: first, using the machine-learning model to predict QoE. Second, according to the QoE prediction, the algorithm manages the video quality of the end-users by offering better video quality. As a result, the proposed algorithm which based on the least absolute shrinkage and selection operator (LASSO) regression is outperformed previously proposed methods for predicting and managing QoE of streaming video over wireless networks.This work has been partially supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" with in the Project under Grant TIN2017-84802-C2-1-P. This study has been partially done in the computer science departments at the (University of Sulaimani and Halabja).Taha, M.; Canovas, A.; Lloret, J.; Ali, A. (2021). A QoE adaptive management system for high definition video streaming over wireless networks. Telecommunication Systems. 77(1):63-81. https://doi.org/10.1007/s11235-020-00741-2638177

    Quality-Oriented Mobility Management for Multimedia Content Delivery to Mobile Users

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    The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently we propose the Smooth Adaptive Soft-Handover Algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections. To estimate the capacity of each connection the novel Quality of Multimedia Streaming (QMS) metric is proposed. The QMS metric aims at offering maximum flexibility and efficiency allowing the applications to fine tune the behavior of the handover algorithm. The current simulation-based performance evaluation clearly shows the better performance of the proposed Smooth Adaptive Soft-Handover Algorithm as compared with other handover solutions. The evaluation was performed in various scenarios including multiple mobile hosts performing handover simultaneously, wireless networks with variable overlapping areas, and various network congestion levels

    Optimizing Perceptual Quality Prediction Models for Multimedia Processing Systems

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    L'abstract è presente nell'allegato / the abstract is in the attachmen
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