931 resultados para Streaming video


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This paper explores the potential for online video as a mechanism to transform the ways students learn, as measured by research, user experience and usage following surveys and trials of patron-driven acquisition collaboratively undertaken by Queensland University of Technology, La Trobe University and Kanopy.

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Video streaming applications have hitherto been supported by single server systems. A major drawback of such a solution is that it increases the server load. The server restricts the number of clients that can be simultaneously supported due to limitation in bandwidth. The constraints of a single server system can be overcome in video streaming if we exploit the endless resources available in a distributed and networked system. We explore a P2P system for streaming video applications. In this paper we build a P2P streaming video (SVP2P) service in which multiple peers co-operate to serve video segments for new requests, thereby reducing server load and bandwidth used. Our simulation shows the playback latency using SVP2P is roughly 1/4th of the latency incurred when the server directly streams the video. Bandwidth consumed for control messages (overhead) is as low as 1.5% of the total data transfered. The most important observation is that the capacity of the SVP2P grows dynamically.

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Purpose: To assess the relationship between student utilization of learning resources, including streaming video (SV), and their performance in the pre-clinical curriculum. [See PDF for complete abstract]

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There is a wide range of telecommunications services that transmit voice, video and data through complex transmission networks and in some cases, the service has not an acceptable quality level for the end user. In this sense the study of methods for assessing video quality and voice have a very important role. This paper presents a classification scheme, based on different criteria, of the methods and metrics that are being studied in recent years. This paper presents how the video quality is affected by degradation in the transmission channel in two kinds of services: Digital TV (ISDB-TB) due the fading in the air interface and video streaming service on an IP network due packet loss. For Digital TV tests was set up a scenario where the digital TV transmitter is connected to an RF channel emulator, where are inserted different fading models and at the end, the videos are saved in a mobile device. The tests of streaming video were performed in an isolated scenario of IP network, which are scheduled several network conditions, resulting in different qualities of video reception. The video quality assessment is performed using objective assessment methods: PSNR, SSIM and VQM. The results show how the losses in the transmission channel affects the quality of end-user experience on both services studied.

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In 2014, eight academic libraries in the state of New York collaborated on a group patron driven acquisition (PDA) pilot program with Kanopy, a video streaming service for libraries. The institutions, despite vast differences in size and profile, each launched Kanopy’s streaming solution on their campuses under a program where they would jointly contribute to and acquire films based on group usage. The pilot ran for seven months and led to some fascinating insights into the differences in demand for film across campuses, the possibility of PDA as a model for library acquisition, and the feasibility of a group approach to acquisition. This paper presents the background to, results of, and reflections on the pilot program from the three unique perspectives of the consortium, the vendor, and one of the libraries involved, providing a holistic view of the success of the pilot and the lessons learned.

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The session explores the potential for “Patron Driven Acquisition” (PDA) as a model for the acquisition of online video. Today, PDA has become a standard model of acquisition in the eBook market, more effectively aligning spend with use and increased return on investment (ROI). PDA is an unexplored model for acquisition of video, for which library collection development is complicated by higher storage and delivery costs, labor overheads for content selection and acquisition, and a dynamic film industry in which media and the technology that supports it is changing daily. Queensland University of Technology (QUT) and La Trobe University in Australia launched a research project in collaboration with Kanopy to explore the opportunity for PDA of video. The study relied on three data sources: (1) national surveys to compare the video purchasing and use practices of colleges, (2) on-campus pilot projects of PDA models to assess user engagement and behavior, and (3) testing of various user applications and features to support the model. The study incorporates usage statistics and survey data and builds upon a peer-reviewed research paper presented at the VALA 2014 conference in Melbourne, Australia. This session will be conducted by the researchers and will graphically present the results from the study. It will map out a future for video PDA, and how libraries can more cost-effectively acquire and maximize the discoverability of online video. The presenters will also solicit input and welcome questions from audience members.

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In November 2010, tension between Internet infrastructure companies boiled over in a dispute between content distribution network (CDN) Level 3 and Internet service provider (ISP) Comcast. Level 3, a distribution partner of Netflix, accused Comcast of violating the principles of net neutrality when the ISP increased distribution fees for carrying high bandwidth services. Comcast justified its actions by stating that the price increase was standard practice and argued Level 3 was trying to avoid paying its fair share. The dispute exemplifies the growing concern over the rising costs of streaming media services. The companies facing these inflated infrastructure costs are CDNs (Level 3, Equinix, Limelight, Akamai, and Voxel), companies that host streaming media content on server farms and distribute the content to a variety of carriers, and ISPs (Comcast, Time Warner, Cox, and AT&T), the cable and phone companies that provide “last mile” service to paying customers. Both CDNs and ISPs are lobbying government regulators to keep their costs at a minimum. The outcome of these disputes will influence the cost, quality, and legal status of streaming media.

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Recent years have witnessed a rapid growth in the demand for streaming video over the Internet, exposing challenges in coping with heterogeneous device capabilities and varying network throughput. When we couple this rise in streaming with the growing number of portable devices (smart phones, tablets, laptops) we see an ever-increasing demand for high-definition videos online while on the move. Wireless networks are inherently characterised by restricted shared bandwidth and relatively high error loss rates, thus presenting a challenge for the efficient delivery of high quality video. Additionally, mobile devices can support/demand a range of video resolutions and qualities. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to available bandwidth and heterogeneity, and can provide us with graceful changes in video quality, all while respecting our viewing satisfaction. In this context the use of well-known scalable media streaming techniques, commonly known as scalable coding, is an attractive solution and the focus of this thesis. In this thesis we investigate the transmission of existing scalable video models over a lossy network and determine how the variation in viewable quality is affected by packet loss. This work focuses on leveraging the benefits of scalable media, while reducing the effects of data loss on achievable video quality. The overall approach is focused on the strategic packetisation of the underlying scalable video and how to best utilise error resiliency to maximise viewable quality. In particular, we examine the manner in which scalable video is packetised for transmission over lossy networks and propose new techniques that reduce the impact of packet loss on scalable video by selectively choosing how to packetise the data and which data to transmit. We also exploit redundancy techniques, such as error resiliency, to enhance the stream quality by ensuring a smooth play-out with fewer changes in achievable video quality. The contributions of this thesis are in the creation of new segmentation and encapsulation techniques which increase the viewable quality of existing scalable models by fragmenting and re-allocating the video sub-streams based on user requirements, available bandwidth and variations in loss rates. We offer new packetisation techniques which reduce the effects of packet loss on viewable quality by leveraging the increase in the number of frames per group of pictures (GOP) and by providing equality of data in every packet transmitted per GOP. These provide novel mechanisms for packetizing and error resiliency, as well as providing new applications for existing techniques such as Interleaving and Priority Encoded Transmission. We also introduce three new scalable coding models, which offer a balance between transmission cost and the consistency of viewable quality.

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Recent years have witnessed a rapid growth in the demand for streaming video over the Internet and mobile networks, exposes challenges in coping with heterogeneous devices and varying network throughput. Adaptive schemes, such as scalable video coding, are an attractive solution but fare badly in the presence of packet losses. Techniques that use description-based streaming models, such as multiple description coding (MDC), are more suitable for lossy networks, and can mitigate the effects of packet loss by increasing the error resilience of the encoded stream, but with an increased transmission byte cost. In this paper, we present our adaptive scalable streaming technique adaptive layer distribution (ALD). ALD is a novel scalable media delivery technique that optimises the tradeoff between streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data are spread amongst all packets, thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the resiliency of the scalable video. The Subjective testing results illustrate that our techniques and models were able to provide levels of consistent high-quality viewing, with lower transmission cost, relative to MDC, irrespective of clip type. This highlights the benefits of selective packetisation in addition to intuitive encoding and transmission.

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Bandwidth constriction and datagram loss are prominent issues that affect the perceived quality of streaming video over lossy networks, such as wireless. The use of layered video coding seems attractive as a means to alleviate these issues, but its adoption has been held back in large part by the inherent priority assigned to the critical lower layers and the consequences for quality that result from their loss. The proposed use of forward error correction (FEC) as a solution only further burdens the bandwidth availability and can negate the perceived benefits of increased stream quality. In this paper, we propose Adaptive Layer Distribution (ALD) as a novel scalable media delivery technique that optimises the tradeoff between the streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data is spread amongst all datagrams thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the scalable video, while providing increased resilience to the highest quality layers. Our experimental results show that ALD improves the perceived quality and also reduces the bandwidth demand by up to 36% in comparison to the well-known Multiple Description Coding (MDC) technique.

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Il lavoro svolto in questa tesi consiste nell'implementare un'applicazione Android per lo streaming video, conforme allo standard MPEG-DASH. L'obiettivo è quello di fornire un valido strumento al fine di eseguire delle analisi sperimentali su algoritmi particolari, detti di rate adaptation. MPEG-Dynamic Adaptive Streaming over Http è uno standard emergente ed è considerato da molti il futuro dello streaming multimediale. Questa tecnologia consente di auto-regolare la qualità del video in base alle condizioni della rete, la capacità del dispositivo o le preferenze dell'utente. Inoltre, essendo uno standard, permette di rendere interoperabili i server e i device dei vari fornitori di contenuti multimediali. Nei primi capitoli introduttivi verrà presentato lo standard e i lavori correlati, successivamente verrà descritta la mia proposta applicativa: DashPlayer. In conclusione, verrà compiuta una valutazione sperimentali sugli algoritmi sopracitati che costituiscono la parte logico-funzionale dell'applicazione.

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Panoramica di MPEG-DASH e TVWS, descrizione dell'implementazione di un middleware multi-interfaccia per lo streaming video adattivo e test di valutazione del lavoro svolto

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Lo streaming è una tecnica per trasferire contenuti multimediali sulla rete globale, utilizzato per esempio da servizi come YouTube e Netflix; dopo una breve attesa, durante la quale un buffer di sicurezza viene riempito, l'utente può usufruire del contenuto richiesto. Cisco e Sandvine, che con cadenza regolare pubblicano bollettini sullo stato di Internet, affermano che lo streaming video ha, e avrà sempre di più, un grande impatto sulla rete globale. Il buon design delle applicazioni di streaming riveste quindi un ruolo importante, sia per la soddisfazione degli utenti che per la stabilità dell'infrastruttura. HTTP Adaptive Streaming indica una famiglia di implementazioni volta a offrire la migliore qualità video possibile (in termini di bit rate) in funzione della bontà della connessione Internet dell'utente finale: il riproduttore multimediale può cambiare in ogni momento il bit rate, scegliendolo in un insieme predefinito, adattandosi alle condizioni della rete. Per ricavare informazioni sullo stato della connettività, due famiglie di metodi sono possibili: misurare la velocità di scaricamento dei precedenti trasferimenti (approccio rate-based), oppure, come recentemente proposto da Netflix, utilizzare l'occupazione del buffer come dato principale (buffer-based). In questo lavoro analizziamo algoritmi di adattamento delle due famiglie, con l'obiettivo di confrontarli su metriche riguardanti la soddisfazione degli utenti, l'utilizzo della rete e la competizione su un collo di bottiglia. I risultati dei nostri test non definiscono un chiaro vincitore, riconoscendo comunque la bontà della nuova proposta, ma evidenziando al contrario che gli algoritmi buffer-based non sempre riescono ad allocare in modo imparziale le risorse di rete.

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Internet è la rete globale a cui si può avere accesso in modo estremamente facile, consentendo praticamente a chiunque di inserire i propri contenuti in tempi rapidi, a costi quasi nulli e senza limitazioni geografiche. Il progresso tecnologico e la maggiore disponibilità della banda larga, uniti alle nuove modalità di fruizione ed ai nuovi format, hanno portato ben il 70% degli web users a vedere video online regolarmente. La popolarità dei servizi di streaming video è cresciuta rapidamente, tanto da registrare dei dati di traffico impressionanti negli ultimi due anni. Il campo applicativo della tesi è Twitch, il più celebre servizio di streaming che è riuscito ad imporsi come quarto sito negli Stati Uniti per traffico Internet: un dato sorprendente se pensiamo che si occupa solo di videogiochi. Il fenomeno Twitch è destinato a durare, lo dimostrano i 970 milioni di dollari investiti da Amazon nel 2014 per acquistare la piattaforma, diventata così una sussidiaria di Amazon. L'obiettivo della tesi è stato lo studio di mercato della piattaforma, attraverso il recupero e l'analisi delle informazioni reperibili in letteratura, nonché attraverso estrapolazione di dati originari mediante le API del sito. Si è proceduto all’analisi delle caratteristiche del mercato servito, in termini di segmentazione effettiva, rivolta alla messa in evidenza della possibile dipendenza dai comportamenti dei player, con particolare attenzione alla possibile vulnerabilità.

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Actualmente la optimization de la calidad de experiencia (Quality of Experience- QoE) de HTTP Adaptive Streaming (HAS) de video recibe una atención creciente. Este incremento de interés proviene fundamentalmente de las carencias de las soluciones actuales HAS, que, al no ser QoE-driven, no incluyen la percepción de la calidad de los usuarios finales como una parte integral de la lógica de adaptación. Por lo tanto, la obtención de información de referencia fiable en QoE en HAS presenta retos importantes, ya que las metodologías de evaluación subjetiva de la calidad de vídeo propuestas en las normas actuales no son adecuadas para tratar con la variación temporal de la calidad que es consustancial de HAS. Esta tesis investiga la influencia de la adaptación dinámica en la calidad de la transmisión de vídeo considerando métodos de evaluación subjetiva. Tras un estudio exhaustivo del estado del arte en la evaluación subjetiva de QoE en HAS, se han resaltado los retos asociados y las líneas de investigación abiertas. Como resultado, se han seleccionado dos líneas principales de investigación: el análisis del impacto en la QoE de los parámetros de las técnicas de adaptación y la investigación de las metodologías de prueba subjetiva adecuada para evaluación de QoE en HAS. Se han llevado a cabo un conjunto de experimentos de laboratorio para investigar las cuestiones planteadas mediante la utilización de diferentes metodologáas para pruebas subjetivas. El análisis estadístico muestra que no son robustas todas las suposiciones y reivindicaciones de las referencias analizadas, en particular en lo que respecta al impacto en la QoE de la frecuencia de las variaciones de calidad, de las adaptaciones suaves o abruptas y de las oscilaciones de calidad. Por otra parte, nuestros resultados confirman la influencia de otros parámetros, como la longitud de los segmentos de vídeo y la amplitud de las oscilaciones de calidad. Los resultados también muestran que tomar en consideración las características objetivas de los contenidos puede ser beneficioso para la mejora de la QoE en HAS. Además, todos los resultados han sido validados mediante extensos análisis experimentales que han incluido estudio tanto en otros laboratorios como en crowdsourcing Por último, sobre los aspectos metodológicos de las pruebas subjetivas de QoE, se ha realizado la comparación entre los resultados experimentales obtenidos a partir de un método estandarizado basado en estímulos cortos (ACR) y un método semi continuo (desarrollado para la evaluación de secuencias prolongadas de vídeo). A pesar de algunas diferencias, el resultado de los análisis estadísticos no muestra ningún efecto significativo de la metodología de prueba. Asimismo, aunque se percibe la influencia de la presencia de audio en la evaluación de degradaciones del vídeo, no se han encontrado efectos estadísticamente significativos de dicha presencia. A partir de la ausencia de influencia del método de prueba y de la presencia de audio, se ha realizado un análisis adicional sobre el impacto de realizar comparaciones estadísticas múltiples en niveles estadísticos de importancia que aumentan la probabilidad de los errores de tipo-I (falsos positivos). Nuestros resultados muestran que, para obtener un efectos sólido en el análisis estadístico de los resultados subjetivos, es necesario aumentar el número de sujetos de las pruebas claramente por encima de los tamaños de muestras propuestos por las normas y recomendaciones actuales. ABSTRACT Optimizing the Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) is receiving increasing attention nowadays. The growth of interest is mainly caused by the fact that current HAS solutions are not QoE-driven, i.e. end-user quality perception is not integral part of the adaptation logic. However, obtaining the necessary reliable ground truths on HAS QoE faces substantial challenges, since the subjective video quality assessment methodologies as proposed by current standards are not well-suited for dealing with the time-varying quality properties that are characteristic for HAS. This thesis investigates the influence of dynamic quality adaptation on the QoE of streaming video by means of subjective evaluation approaches. Based on a comprehensive survey of related work on subjective HAS QoE assessment, the related challenges and open research questions are highlighted and discussed. As a result, two main research directions are selected for further investigation: analysis of the QoE impact of different technical adaptation parameters, and investigation of testing methodologies suitable for HAS QoE evaluation. In order to investigate related research issues and questions, a set of laboratory experiments have been conducted using different subjective testing methodologies. Our statistical analysis demonstrates that not all assumptions and claims reported in the literature are robust, particularly as regards the QoE impact of switching frequency, smooth vs. abrupt switching, and quality oscillation. On the other hand, our results confirm the influence of some other parameters such as chunk length and switching amplitude on perceived quality. We also show that taking the objective characteristics of the content into account can be beneficial to improve the adaptation viewing experience. In addition, all aforementioned findings are validated by means of an extensive cross-experimental analysis that involves external laboratory and crowdsourcing studies. Finally, to address the methodological aspects of subjective QoE testing, a comparison between the experimental results obtained from a (short stimuli-based) ACR standardized method and a semi-continuous method (developed for assessment of long video sequences) has been performed. In spite of observation of some differences, the result of statistical analysis does not show any significant effect of testing methodology. Similarly, although the influence of audio presence on evaluation of video-related degradations is perceived, no statistically significant effect of audio presence could be found. Motivating by this finding (no effect of testing method and audio presence), a subsequent analysis has been performed investigating the impact of performing multiple statistical comparisons on statistical levels of significance which increase the likelihood of Type-I errors (false positives). Our results show that in order to obtain a strong effect from the statistical analysis of the subjective results, it is necessary to increase the number of test subjects well beyond the sample sizes proposed by current quality assessment standards and recommendations.