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Academic literature on the topic 'Video Quality Measure'

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Published: 14 March 2023

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Journal articles on the topic "Video Quality Measure"

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Barkowsky, Marcus, Jens Bialkowski, BjÖrn Eskofier, Roland Bitto, and AndrÉ Kaup. "Temporal Trajectory Aware Video Quality Measure." IEEE Journal of Selected Topics in Signal Processing 3, no. 2 (April 2009): 266–79. http://dx.doi.org/10.1109/jstsp.2009.2015375.

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Hekstra, A. P., J. G. Beerends, D. Ledermann, F. E. de Caluwe, S. Kohler, R. H. Koenen, S. Rihs, M. Ehrsam, and D. Schlauss. "PVQM – A perceptual video quality measure." Signal Processing: Image Communication 17, no. 10 (November 2002): 781–98. http://dx.doi.org/10.1016/s0923-5965(02)00056-5.

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Arndt, Sebastian, Jan-Niklas Antons, Robert Schleicher, Sebastian Moller, and Gabriel Curio. "Using Electroencephalography to Measure Perceived Video Quality." IEEE Journal of Selected Topics in Signal Processing 8, no. 3 (June 2014): 366–76. http://dx.doi.org/10.1109/jstsp.2014.2313026.

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Dumic, Emil, and Anamaria Bjelopera. "No-Reference Objective Video Quality Measure for Frame Freezing Degradation." Sensors 19, no. 21 (October 26, 2019): 4655. http://dx.doi.org/10.3390/s19214655.

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In this paper we present a novel no-reference video quality measure, NR-FFM (no-reference frame–freezing measure), designed to estimate quality degradations caused by frame freezing of streamed video. The performance of the measure was evaluated using 40 degraded video sequences from the laboratory for image and video engineering (LIVE) mobile database. Proposed quality measure can be used in different scenarios such as mobile video transmission by itself or in combination with other quality measures. These two types of applications were presented and studied together with considerations on relevant normalization issues. The results showed promising correlation values between the user assigned quality and the estimated quality scores.
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Li, Gang, Ainiwaer Aizimaiti, and Yan Liu. "Quaternion Model of Fast Video Quality Assessment Based on Structural Similarity Normalization." Applied Mechanics and Materials 380-384 (August 2013): 3982–85. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3982.

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Video quality evaluation methods have been widely studied because of an increasing need in variety of video processing applications, such as compression, analysis, communication, enhancement and restoration. The quaternion models are also widely used to measure image or video quality. In this paper, we proposed a new quaternion model which mainly describes the contour feature, surface feature and temporal information of the video. We use structure similarity comparison to normalize four quaternion parts respectively, because each part of the quaternion use different metric. Structure similarity comparison is also used to measure the difference between reference videos and distortion videos. The results of experiments show that the new method has good correlation with perceived video quality when tested on the video quality experts group (VQEG) Phase I FR-TV test data set.
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Leszczuk, Mikołaj, Lucjan Janowski, Jakub Nawała, and Atanas Boev. "Objective Video Quality Assessment Method for Face Recognition Tasks." Electronics 11, no. 8 (April 7, 2022): 1167. http://dx.doi.org/10.3390/electronics11081167.

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Nowadays, there are many metrics for overall Quality of Experience (QoE), both those with Full Reference (FR), such as Peak Signal-to-Noise Ratio (PSNR) or Structural Similarity (SSIM), and those with No Reference (NR), such as Video Quality Indicators (VQI), which are successfully used in video processing systems to evaluate videos whose quality is degraded by different processing scenarios. However, they are not suitable for video sequences used for recognition tasks (Target Recognition Videos, TRV). Therefore, correctly estimating the performance of the video processing pipeline in both manual and Computer Vision (CV) recognition tasks is still a major research challenge. There is a need for objective methods to evaluate video quality for recognition tasks. In response to this need, we show in this paper that it is possible to develop the new concept of an objective model for evaluating video quality for face recognition tasks. The model is trained, tested and validated on a representative set of image sequences. The set of degradation scenarios is based on the model of a digital camera and how the luminous flux reflected from the scene eventually becomes a digital image. The resulting degraded images are evaluated using a CV library for face recognition as well as VQI. The measured accuracy of a model, expressed as the value of the F-measure parameter, is 0.87.
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Alsrehin, Nawaf O., and Ahmad F. Klaib. "VMQ: an algorithm for measuring the Video Motion Quality." Bulletin of Electrical Engineering and Informatics 8, no. 1 (March 1, 2019): 231–38. http://dx.doi.org/10.11591/eei.v8i1.1418.

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This paper proposes a new full-reference algorithm, called Video Motion Quality (VMQ) that evaluates the relative motion quality of the distorted video generated from the reference video based on all the frames from both videos. VMQ uses any frame-based metric to compare frames from the original and distorted videos. It uses the time stamp for each frame to measure the intersection values. VMQ combines the comparison values with the intersection values in an aggregation function to produce the final result. To explore the efficiency of the VMQ, we used a set of raw, uncompressed videos to generate a new set of encoded videos. These encoded videos are then used to generate a new set of distorted videos which have the same video bit rate and frame size but with reduced frame rate. To evaluate the VMQ, we applied the VMQ by comparing the encoded videos with the distorted videos and recorded the results. The initial evaluation results showed compatible trends with most of subjective evaluation results.
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Moore, Peter Thomas, Neil O’Hare, Kevin P. Walsh, Neil Ward, and Niamh Conlon. "Objective video quality measure for application to tele-echocardiography." Medical & Biological Engineering & Computing 46, no. 8 (July 10, 2008): 807–13. http://dx.doi.org/10.1007/s11517-008-0364-5.

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Wu, Xuanyi, Irene Cheng, Zhenkun Zhou, and Anup Basu. "RAVA: Region-Based Average Video Quality Assessment." Sensors 21, no. 16 (August 15, 2021): 5489. http://dx.doi.org/10.3390/s21165489.

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Video has become the most popular medium of communication over the past decade, with nearly 90 percent of the bandwidth on the Internet being used for video transmission. Thus, evaluating the quality of an acquired or compressed video has become increasingly important. The goal of video quality assessment (VQA) is to measure the quality of a video clip as perceived by a human observer. Since manually rating every video clip to evaluate quality is infeasible, researchers have attempted to develop various quantitative metrics that estimate the perceptual quality of video. In this paper, we propose a new region-based average video quality assessment (RAVA) technique extending image quality assessment (IQA) metrics. In our experiments, we extend two full-reference (FR) image quality metrics to measure the feasibility of the proposed RAVA technique. Results on three different datasets show that our RAVA method is practical in predicting objective video scores.
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Hasan, Md Mehedi, Md Ariful Islam, Sejuti Rahman, Michael R. Frater, and John F. Arnold. "No-Reference Quality Assessment of Transmitted Stereoscopic Videos Based on Human Visual System." Applied Sciences 12, no. 19 (October 7, 2022): 10090. http://dx.doi.org/10.3390/app121910090.

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Provisioning the stereoscopic 3D (S3D) video transmission services of admissible quality in a wireless environment is an immense challenge for video service providers. Unlike for 2D videos, a widely accepted No-reference objective model for assessing transmitted 3D videos that explores the Human Visual System (HVS) appropriately has not been developed yet. Distortions perceived in 2D and 3D videos are significantly different due to the sophisticated manner in which the HVS handles the dissimilarities between the two different views. In real-time video transmission, viewers only have the distorted or receiver end content of the original video acquired through the communication medium. In this paper, we propose a No-reference quality assessment method that can estimate the quality of a stereoscopic 3D video based on HVS. By evaluating perceptual aspects and correlations of visual binocular impacts in a stereoscopic movie, the approach creates a way for the objective quality measure to assess impairments similarly to a human observer who would experience the similar material. Firstly, the disparity is measured and quantified by the region-based similarity matching algorithm, and then, the magnitude of the edge difference is calculated to delimit the visually perceptible areas of an image. Finally, an objective metric is approximated by extracting these significant perceptual image features. Experimental analysis with standard S3D video datasets demonstrates the lower computational complexity for the video decoder and comparison with the state-of-the-art algorithms shows the efficiency of the proposed approach for 3D video transmission at different quantization (QP 26 and QP 32) and loss rate (1% and 3% packet loss) parameters along with the perceptual distortion features.
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Dissertations / Theses on the topic "Video Quality Measure"

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Pettersson, Johan, and Robin Veteläinen. "A comparison of solutions to measure Quality of Service for video streams." Thesis, KTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188514.

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There are more and more people watching video streams over the Internet, and this has led to an increase in companies that compete for viewers. To improve the users experience, these companies can measure how their services are performing. The aim of this thesis was to recommend a way to measure the quality of service for a real time video streaming service. Three methods were presented; to buy the information from a content delivery network, extend existing analytics software or build a custom solution using packet sniffing. It was decided to extend existing analytics software. An evaluation was made on which software to extend. Four solutions were compared: Google Analytics, Mixpanel, Ooyala IQ and Piwik. The comparison was made using the analytic hierarchy process, comparing each alternative in their performance in criteria such as API maturity, flexibility, visualization and support. The recommended software to extend when building a real time video streaming service is Ooyala IQ which excel at flexibility and is easy to implement into existing solutions. It also had great capacity, offering no limit on how many events it can track per month, and finally it offers great dedicated support via telephone or email.
Det finns fler och fler personer som tittar på video strömmar på Internet, detta har lett till att nya företag har startats som konkurerar om tittare. För att förbättra kundupplevelsen kan man mäta hur tjänsten presterar. Målet med examensarbetet var att rekommendera hur man kan mäta tjänstekvalite för en realtidsvideoströmningstjänst. Tre olika lösningsförslag presenterades; att köpa informationen från en content delivery network, att bygga vidare på tillgängliga analytisk mjukvara eller att bygga ett eget paketsniffarprogram. Det bestämdes att bygga vidare på tillgänglig analytisk mjukvara. Fyra olika mjukvara jämfördes: Google Analytics, Mixpanel, Ooyala IQ och Piwik. Jämförelsen gjordes med hjälp av analytical hierarchy process, de olika alternativen jämfördes med avseende på: hur moget API:et var, flexibilitet, visualiseringen av data och support. Rekommendationen är att använda sig av Ooyala IQ som utmärker sig med avseende på flexibilitet, det var enkelt att använda deras API i sin egen lösning, det fanns ingen gräns på hur många händelser man kunde lagra per månad, och slutligen så fanns det dedikerad supportpersonal att nå via telefon eller email.
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Intawong, Kannikar. "Analyse automatique de la circulation automobile par vidéosurveillance routière." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2081.

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Cette thèse s’inscrit dans le contexte de l’analyse vidéo du trafic routier. Dans certaines grandes villes, des centaines de caméras produisent de très grandes quantités de données, impossible à manipuler sans traitement automatique. Notre principal objectif est d'aider les opérateurs humains en analysant automatiquement les données vidéo. Pour aider les contrôleurs de la circulation à prendre leurs décisions, il est important de connaître en temps réel, l'état du trafic (nombre de véhicules et vitesse des véhicules sur chaque segment de voie), mais aussi de disposer de statistiques temporelles tout au long de la journée, de la semaine, de la saison ou de l'année. Les caméras ont été déployées depuis longtemps pour le trafic et pour d'autres fins de surveillance, car elles fournissent une source d'information riche pour la compréhension humaine. L'analyse vidéo peut désormais apporter une valeur ajoutée aux caméras en extrayant automatiquement des informations pertinentes. De cette façon, la vision par ordinateur et l'analyse vidéo deviennent de plus en plus importantes pour les systèmes de transport intelligents (intelligent transport systems : ITSs). L’une des problématiques abordées dans cette thèse est liée au comptage automatique de véhicules. Pour être utile, un système de surveillance vidéo doit être entièrement automatique et capable de fournir, en temps réel, l'information qui concerne le comportement de l'objet dans la scène. Nous pouvons obtenir ces renseignements sur la détection et le suivi des objets en mouvement dans les vidéos, ce qui a été un domaine largement étudié. Néanmoins, la plupart des systèmes d'analyse automatique par vidéo ont des difficultés à gérer les situations particulières. Aujourd'hui, il existe de nombreux défis à résoudre tels que les occultations entre les différents objets, les arrêts longs, les changements de luminosité, etc… qui conduisent à des trajectoires incomplètes. Dans la chaîne de traitements que nous proposons, nous nous sommes concentrés sur l'extraction automatique de statistiques globales dans les scènes de vidéosurveillance routière. Notre chaîne de traitements est constituée par les étapes suivantes : premièrement, nous avons évalué différentes techniques de segmentation de vidéos et de détection d'objets en mouvement. Nous avons choisi une méthode de segmentation basée sur une version paramétrique du mélange de gaussiennes appliquée sur une hiérarchie de blocs, méthode qui est considérée actuellement comme l'un des meilleurs procédés pour la détection d'objets en mouvement. Nous avons proposé une nouvelle méthodologie pour choisir les valeurs optimales des paramètres d’un algorithme permettant d’améliorer la segmentation d’objets en utilisant des opérations morphologiques. Nous nous sommes intéressés aux différents critères permettant d’évaluer la qualité d’une segmentation, résultant d’un compromis entre une bonne détection des objets en mouvement, et un faible nombre de fausses détections, par exemple causées par des changements d’illumination, des reflets ou des bruits d’acquisition. Deuxièmement, nous effectuons une classification des objets, basée sur les descripteurs de Fourier, et nous utilisons ces descripteurs pour éliminer les objets de type piétons ou autres et ne conserver que les véhicules. Troisièmement, nous utilisons un modèle de mouvement et un descripteur basé sur les couleurs dominantes pour effectuer le suivi des objets extraits. En raison des difficultés mentionnées ci-dessus, nous obtenons des trajectoires incomplètes, qui donneraient une information de comptage erronée si elles étaient exploitées directement. Nous proposons donc d’agréger les données partielles des trajectoires incomplètes et de construire une information globale sur la circulation des véhicules dans la scène. Notre approche permet la détection des points d’entrée et de sortie dans les séquences d’images. Nous avons testé nos algorithmes sur des données privées provenant
This thesis is written in the context of video traffic analysis. In several big cities, hundreds of cameras produce very large amounts of data, impossible to handle without automatic processing. Our main goal is to help human operators by automatically analyzing video data. To help traffic controllers make decisions, it is important to know the traffic status in real time (number of vehicles and vehicle speed on each path), but also to dispose of traffic statistics along the day, week, season or year. The cameras have been deployed for a long time for traffic and other monitoring purposes, because they provide a rich source of information for human comprehension. Video analysis can automatically extract relevant information. Computer vision and video analysis are becoming more and more important for Intelligent Transport Systems (ITSs). One of the issues addressed in this thesis is related to automatic vehicle counting. In order to be useful, a video surveillance system must be fully automatic and capable of providing, in real time, information concerning the behavior of the objects in the scene. We can get this information by detection and tracking of moving objects in videos, a widely studied field. However, most automated video analysis systems do not easily manage particular situations.Today, there are many challenges to be solved, such as occlusions between different objects, long stops of an object in the scene, luminosity changes, etc., leading to incomplete trajectories of moving objects detected in the scene. We have concentrated our work on the automatic extraction of global statistics in the scenes. Our workflow consists of the following steps: first, we evaluated different methods of video segmentation and detection of moving objects. We have chosen a segmentation method based on a parametric version of the Mixture of Gaussians, applied to a hierarchy of blocks, which is currently considered one of the best methods for the detection of moving objects. We proposed a new methodology to choose the optimal parameter values of an algorithm to improve object segmentation by using morphological operations. We were interested in the different criteria for evaluating the segmentation quality, resulting from a compromise between a good detection of moving objects, and a low number of false detections, for example caused by illumination changes, reflections or acquisition noises. Secondly, we performed an objects classification, based on Fourier descriptors, and we use these descriptors to eliminate pedestrian or other objects and retain only vehicles. Third, we use a motion model and a descriptor based on the dominant colors to track the extracted objects. Because of the difficulties mentioned above, we obtain incomplete trajectories, which, exploited as they are, give incorrect counting information. We therefore proposed to aggregate the partial data of the incomplete trajectories and to construct a global information on the vehicles circulation in the scene. Our approach allows to detect input and output points in image sequences. We tested our algorithms on private data from the traffic control center in Chiang Mai City, Thailand, as well as on MIT public video data. On this last dataset, we compared the performance of our algorithms with previously published articles using the same data. In several situations, we illustrate the improvements made by our method in terms of location of input / output zones, and in terms of vehicle counting
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Saidi, Inès. "Analyse et modélisation de la qualité perçue des applications de visiophonie." Thesis, Rennes, INSA, 2018. http://www.theses.fr/2018ISAR0013/document.

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Dans un contexte fortement concurrentiel, l'un des principaux enjeux pour les opérateurs et les fournisseurs de services de visiophonie est de garantir aux utilisateurs une qualité d'expérience (QoE) optimale. Il existe un fort besoin d'une mesure qui reflète la satisfaction et la perception des utilisateurs de ces services. La qualité audiovisuelle d'un appel vidéo doit être contrôlée pour répondre à deux besoins principaux. Le premier concerne la planification de nouvelles technologies en cours de développement. Le second est axé sur le contrôle des communications existantes en évaluant la qualité des services offerts. Aujourd'hui, deux approches sont utilisées pour évaluer la qualité audiovisuelle : les tests subjectifs en collectant des notes données par des participants sur des échelles de qualité, après visualisation et écoute de séquences audiovisuelles et les métriques objectives basées sur des algorithmes automatiques d'évaluation de la qualité d'un signal audio, vidéo ou audiovisuel. Concernant les services de téléphonie, des décennies de recherche, de standardisation et d'exploitation des réseaux ont permis aux opérateurs de maîtriser les outils de diagnostic et de déterminer les métriques représentatives de la qualité vocale. Cependant, les méthodes de mesure de la qualité audiovisuelle des services conversationnels ne sont pas encore matures et peu exploitées par les opérateurs de télécommunication. Le présent travail est centré sur la recherche de métriques représentatives de la perception de la qualité des nux associés aux services de visiophonie et de visioconférence. Ces métriques objectives sont calculées à partir du signal audio et vidéo. Des tests subjectifs sont menés afin de collecter le jugement des utilisateurs du service sur la qualité perçue en fonction de différents niveaux de dégradations. Nous avons étudié l'impact des conditions réseau (perte de paquet, gigue et désynchronisation) sur la QoE d'un appel vidéo. Le principe général est ensuite d'établir une corrélation forte entre les métriques objectives sélectionnées et la qualité perçue telle qu'elle est exprimée par les utilisateurs. Les résultats ont montré que les nouvelles métriques de qualité globale audiovisuelle qui prennent en compte l'aspect temporel de la vidéo sont plus performantes que les métriques basées qualité d'images. D'autre part l'utilisation d'une approche machine learning représente une solution pour générer un modèle de prédiction de la qualité globale à partir des métriques de dégradation (flou, pixellisation, gel d'images, ... )
In a highly competitive environment, one of the key challenges for operators and providers of video telephony services is to ensure the highest quality of experience (QoE). There is a strong need for a measure that reflects users satisfaction and perception of these services. The audio-visual quality of a video call must be controlled to meet two main needs. The first concerns the planning of new technologies under development. The second is focused on the control of existing communications by assessing the quality of the services offered and evaluating them. Two approaches are used to evaluate audio-visual quality: subjective tests by collecting scores given by participants on quality scales, after viewing and listening to audiovisual sequences and objective metrics based on automatic audio/ video or audiovisual quality evaluation algorithms. Concerning telephony services, decades of research, standardization work and network exploitation, have allowed operators to master the automatic monitoring tools and to determine the representative metrics of voice quality. However, the metrics for measuring the audiovisual quality of a conversational services are not yet mature and not exploited by telecommunication operators. The present work focuses on finding representative metrics of the perception of the video telephony anc videoconferencing services quality. These objective metrics are calculated from the audio and video signals. Subjective tests are conducted to collect the judgment of service users on the perceived quality according to different levels of degradation. We studied the impact of network conditions (packet loss, jitter and desynchronization) on the QoE of a video call. The general principle is then to establish a correlation between the selected objective metrics and the perceived quality as expressed by the users. The results showed that new metric of overall audiovisual quality that take into account the temporal aspect of video are more powerful than image quality based metrics. On the other hand, the use of a machine learning approach represents a solution to generat a global quality prediction model from the degradation metrics (blur, pixelization, image freezing, ... )
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Černoch, Adam. "Vybrané způsoby zlepšení orientace řidiče v dopravním prostoru." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-233053.

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The aim of this thesis is to find suitable measures which will lead to the improvement of driver orientation in traffic spaceleading to lower the accident rate in the area. The theoretical part describes the traffic surveys that relate to the topic. Furthermore, the work mentioned detectors used for the implementation of automated traffic surveys. The theoretical part also describes methods that can be used to analyze the selected location and then design the ideal modification. At the end gives an overview of the various measures. In the practical part are different methodologies used for the analysis of selected intersections. Firstly, the analysis of observed conflict situations, including making conflicting diagram, under which was designed to measure. Then, the analysis of traffic accidents. Again, the result was a proposal for possible actions. The main objective was to compare and appreciation of both methodologies and proces design measures to improve driver orientation in the selected location.
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GrigoryKuritsyn and 柯高瑞. "Service Quality in Video Surveillance-as-a-Service: Developing Measures and Analyzing Its Function in Continuance Usage Intention." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/91460510252474392991.

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碩士
國立成功大學
國際經營管理研究所碩士在職專班
102
Video surveillance is one of the most important components of the complete security solution. With the development of the Internet and technologies this important piece of safety is available for average customers not only locally, but also remotely with the help of cloud computing technologies. In the scientific works there are no studies that cover this topic so far. This research aims to find the major factors that will affect customers’ perception of the service quality, and reasons that will drive customers to keep using the service. As it was found, trust can play an important role in identifying the continuance intention to use services; and the seven major factors of VSaaS quality (rapport, reliability, responsiveness, flexibility, features, security, and privacy) would be the major players in defining quality, and hence perceived usefulness and continuous intention to use the services.
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Books on the topic "Video Quality Measure"

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L, Warholak Terri, and Nau David P, eds. Quality and safety in pharmacy practice. New York: McGraw-Hill, 2010.

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Cohen, Marcy. Playing with our health: Hazards in the automated office. Vancouver: Women's Skill Development Society, 1986.

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Montana. Legislature. Office of the Legislative Auditor. Performance audit report: Regulation and monitoring of video gambling machines, Department of Justice, Gambling Control Division. Helena, Mont: The Office, 1994.

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Montana. Legislature. Office of the Legislative Auditor. Performance audit report: Air quality program, Department of Health and Environmental Sciences. Helena, Mont: The Office, 1994.

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Montana. Legislature. Office of the Legislative Auditor. Performance audit report: Enforcement of the water quality and the public water supply acts. Helena, Mont: The Office, 1994.

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Auditor, Montana Legislature Office of the Legislative. Performance audit report: Controls over use of state telephones. Helena, Mont: The Office, 1986.

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Auditor, Montana Legislature Office of the Legislative. Performance audit report: Automated system development and maintenance, Department of Administration, Department of Social and Rehabilitation Services, Department of Labor and Industry. Helena, Mont: The Office, 1993.

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Montana. Legislature. Office of the Legislative Auditor. Performance audit report: Space utilization and records management, Helena-located state agencies. Helena, Mont. (Room 135, State Capitol 59620): The Office, 1989.

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Montana. Legislature. Office of the Legislative Auditor. Performance audit report: Treasury Bureau, Department of Administration. Helena (Rm. 135, State Capitol, Helena 59620): Office of the Legislative Auditor, 1989.

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Montana. Legislature. Office of the Legislative Auditor. Performance audit report: Foster care facility licensing and other related issues, Department of Family Services. Helena, Mont: The Office, 1993.

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Book chapters on the topic "Video Quality Measure"

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Budescu, Bogdan, Alexandru Căliman, and Mihai Ivanovici. "The Correlation Dimension: A Video Quality Measure." In Mobile Multimedia Communications, 55–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30419-4_5.

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El Khattabi, Hasnaa, Ahmed Tamtaoui, and Driss Aboutajdine. "Measure a Subjective Video Quality Via a Neural Network." In Communications in Computer and Information Science, 121–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21984-9_11.

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Noor, Norliza Mohd, Omar Mohd Rijal, Joel Chia Ming Than, Rosminah M. Kassim, and Ashari Yunus. "Regression as a Tool to Measure Segmentation Quality and Preliminary Indicator of Diseased Lungs." In Image and Video Technology, 502–11. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29451-3_40.

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Kramer, Maria, Julia Stürmer, Christian Förtsch, Tina Seidel, Stefan Ufer, Martin R. Fischer, and Birgit J. Neuhaus. "Diagnosing the Instructional Quality of Biology Lessons Based on Staged Videos: Developing DiKoBi, A Video-Based Simulation." In Learning to Diagnose with Simulations, 63–81. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89147-3_6.

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AbstractIdentifying and interpreting challenging instructional situations is important for teacher performance in the classroom, thus also for instructional quality. This project examines classroom situations in which pre-service teachers diagnose effective teaching in terms of instructional quality in the context of biology lessons. The interdisciplinary collaboration combines expertise in research on teachers’ professional competence, video-based teaching, and computer-supported case-based learning in several contexts. The video-based simulation DiKoBi (German acronym for “diagnostic competences of biology teachers in biology classrooms”) was developed to investigate, measure, and foster pre-service teachers’ diagnostic skills concerning the instructional quality of biology lessons. Staged videos embedded in the video-based simulation DiKoBi show six different classroom situations, each focusing on one biology-specific instructional quality feature. Validity of the content and tasks in DiKoBi were examined in interviews using think-aloud protocols and expert-novice comparisons. In future research, intervention studies will be used to analyze the effects of knowledge acquisition and scaffolding during teachers’ diagnosing on their diagnostic skills concerning instructional quality.
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Ghosh, Monalisa, and Chetna Singhal. "Machine Learning-Based Subjective Quality Estimation for Video Streaming Over Wireless Networks." In Advances in Wireless Technologies and Telecommunication, 235–54. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7458-3.ch010.

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Video streaming services top the internet traffic surging forward a competitive environment to impart best quality of experience (QoE) to the users. The standard codecs utilized in video transmission systems eliminate the spatiotemporal redundancies in order to decrease the bandwidth requirement. This may adversely affect the perceptual quality of videos. To rate a video quality both subjective and objective parameters can be used. So, it is essential to construct frameworks which will measure integrity of video just like humans. This chapter focuses on application of machine learning to evaluate the QoE without requiring human efforts with higher accuracy of 86% and 91% employing the linear and support vector regression respectively. Machine learning model is developed to forecast the subjective quality of H.264 videos obtained after streaming through wireless networks from the subjective scores.
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"Secret Communication Techniques." In Advanced Digital Image Steganography Using LSB, PVD, and EMD, 1–19. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7516-0.ch001.

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This chapter introduces the reader to cryptography, steganography, watermarking, and quality parameters of image steganography techniques. Cryptography is a technique for secret communication. Steganography is a technique for secret and unnoticeable communication. The watermarking techniques hide watermarks inside the digital media. There are four types of steganography techniques: (1) image steganography, (2) audio steganography, (3) video steganography, and (4) text steganography. The quality of image steganographic algorithms can be measured by three parameters like (1) hiding capacity, (2) distortion measure, and (3) security check.
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Cavallaro, Andrea, and Stefan Winkler. "Perceptual Semantics." In Multimedia Technologies, 1441–55. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-953-3.ch105.

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The design of image and video compression or transmission systems is driven by the need for reducing the bandwidth and storage requirements of the content while maintaining its visual quality. Therefore, the objective is to define codecs that maximize perceived quality as well as automated metrics that reliably measure perceived quality. One of the common shortcomings of traditional video coders and quality metrics is the fact that they treat the entire scene uniformly, assuming that people look at every pixel of the image or video. In reality, we focus only on particular areas of the scene. In this chapter, we prioritize the visual data accordingly in order to improve the compression performance of video coders and the prediction performance of perceptual quality metrics. The proposed encoder and quality metric incorporate visual attention and use a semantic segmentation stage, which takes into account certain aspects of the cognitive behavior of people when watching a video. This semantic model corresponds to a specific human abstraction, which need not necessarily be characterized by perceptual uniformity. In particular, we concentrate on segmenting moving objects and faces, and we evaluate the perceptual impact on video coding and on quality evaluation.
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Cavallaro, Andrea, and Stefan Winkler. "Perceptual Semantics." In Digital Multimedia Perception and Design, 1–20. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-860-4.ch001.

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The design of image and video compression or transmission systems is driven by the need for reducing the bandwidth and storage requirements of the content while maintaining its visual quality. Therefore, the objective is to define codecs that maximize perceived quality as well as automated metrics that reliably measure perceived quality. One of the common shortcomings of traditional video coders and quality metrics is the fact that they treat the entire scene uniformly, assuming that people look at every pixel of the image or video. In reality, we focus only on particular areas of the scene. In this chapter, we prioritize the visual data accordingly in order to improve the compression performance of video coders and the prediction performance of perceptual quality metrics. The proposed encoder and quality metric incorporate visual attention and use a semantic segmentation stage, which takes into account certain aspects of the cognitive behavior of people when watching a video. This semantic model corresponds to a specific human abstraction, which need not necessarily be characterized by perceptual uniformity. In particular, we concentrate on segmenting moving objects and faces, and we evaluate the perceptual impact on video coding and on quality evaluation.
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Sankisa, Arun, Katerina Pandremmenou, Peshala V. Pahalawatta, Lisimachos P. Kondi, and Aggelos K. Katsaggelos. "SSIM-Based Distortion Estimation for Optimized Video Transmission over Inherently Noisy Channels." In Biometrics, 690–709. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0983-7.ch028.

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The authors present two methods for examining video quality using the Structural Similarity (SSIM) index: Iterative Distortion Estimate (IDE) and Cumulative Distortion using SSIM (CDSSIM). In the first method, three types of slices are iteratively reconstructed frame-by-frame for three different combinations of packet loss and the resulting distortions are combined using their probabilities to give the total expected distortion. In the second method, a cumulative measure of the overall distortion is computed by summing the inter-frame propagation impact to all frames affected by a slice loss. Furthermore, the authors develop a No-Reference (NR) sparse regression framework for predicting the CDSSIM metric to circumvent the real-time computational complexity in streaming video applications. The two methods are evaluated in resource allocation and packet prioritization schemes and experimental results show improved performance and better end-user quality. The accuracy of the predicted CDSSIM values is studied using standard performance measures and a Quartile-Based Prioritization (QBP) scheme.
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Duarte, Abraham, Angel Sanchez, Felipe Fernandez, and Antonio S. Montemayor. "A Graph-Based Image Segmentation Alorithm Using Heirarchical Social Metaheuristic." In Advances in Image and Video Segmentation, 72–92. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-753-9.ch004.

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This chapter proposes a new evolutionary graph-based image segmentation method to improve quality results. Our approach is quite general and can be considered as a pixel- or region-based segmentation technique. What is more important is that they (pixels or regions) are not necessarily adjacent. We start from an image described by a simplified undirected weighted graph where nodes represent either pixels or regions (obtained after an oversegmentation process) and weighted edges measure the dissimilarity between pairs of pixels or regions. As a second phase, the resulting graph is successively partitioned into two subgraphs in a hierarchical fashion, corresponding to the two most significant components of the actual image, until a termination condition is met. This graph-partitioning task is solved as a variant of the min-cut problem (normalized cut) using a hierarchical social (HS) metaheuristic. As a consequence of this iterative graph bipartition stage, pixels or regions are initially merged into the two most coherent components, which are successively bipartitioned according to this graph-splitting scheme. We applied the proposed approach to brightness segmentation on different standard test images, with good visual and objective segmentation quality results.
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Conference papers on the topic "Video Quality Measure"

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Pyko, Sergey, Boris Filippov, Tamar Shoham, Dror Gill, Nikolay Terterov, Alexander Ivanov, and Vadim Demidov. "Porting BQM perceptual video quality measure to hardware." In MHV '22: Mile-High Video Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3510450.3517278.

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Li, Songnan, Lin Ma, Fan Zhang, and King Ngi Ngan. "Temporal inconsistency measure for video quality assessment." In 2010 Picture Coding Symposium (PCS). IEEE, 2010. http://dx.doi.org/10.1109/pcs.2010.5702572.

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Kim, Wonjun, and Changick Kim. "Video quality measure for mobile IPTV service." In Optical Engineering + Applications, edited by Andrew G. Tescher. SPIE, 2008. http://dx.doi.org/10.1117/12.799448.

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Bai, Chen, and Amy R. Reibman. "Video Quality Temporal Pooling using a Visibility Measure." In 2019 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2019. http://dx.doi.org/10.1109/icme.2019.00082.

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Okamoto, Jun, Keishiro Watanabe, Aoi Honda, Masato Uchida, and Seiichiro Hangai. "HDTV objective video quality assessment method applying fuzzy measure." In 2009 International Workshop on Quality of Multimedia Experience (QoMEx 2009). IEEE, 2009. http://dx.doi.org/10.1109/qomex.2009.5246958.

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Shadiya, P., and K. P. Balachandran. "A perceptual distortion measure for video quality assessment using wavelet and statistical measures." In 2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES). IEEE, 2015. http://dx.doi.org/10.1109/spices.2015.7091376.

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Kawayoke, Yoshikazu, and Yuukou Horita. "NR objective continuous video quality assessment model based on frame quality measure." In 2008 15th IEEE International Conference on Image Processing. IEEE, 2008. http://dx.doi.org/10.1109/icip.2008.4711772.

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Yao, Susu, Weisi Lin, Eeping Ong, and Zhongkang Lu. "A Wavelet-Based Visible Distortion Measure for Video Quality Evaluation." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.313134.

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Jeong, Dong-ju, Hyoung Jin Yoo, and Nam Ik Cho. "Consumer video summarization based on image quality and representativeness measure." In 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2015. http://dx.doi.org/10.1109/globalsip.2015.7418260.

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Ben Amor, Mohamed, Mohamed Chaker Larabi, Fahmi Kammoun, and Nouri Masmoudi. "A block artifact distortion measure for no reference video quality evaluation." In 2014 First International Image Processing, Applications and Systems Conference (IPAS). IEEE, 2014. http://dx.doi.org/10.1109/ipas.2014.7043326.

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Reports on the topic "Video Quality Measure"

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Lee, Yooyoung, P. Jonathon Phillips, James J. Filliben, J. Ross Beveridge, and Hao Zhang. Identifying face quality and factor measures for video. National Institute of Standards and Technology, May 2014. http://dx.doi.org/10.6028/nist.ir.8004.

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