109 research outputs found

    Near-optimal content replication for interactive multiview video streaming

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    Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

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    Codage réseau pour des applications multimédias avancées

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    Network coding is a paradigm that allows an efficient use of the capacity of communication networks. It maximizes the throughput in a multi-hop multicast communication and reduces the delay. In this thesis, we focus our attention to the integration of the network coding framework to multimedia applications, and in particular to advanced systems that provide enhanced video services to the users. Our contributions concern several instances of advanced multimedia communications: an efficient framework for transmission of a live stream making joint use of network coding and multiple description coding; a novel transmission strategy for lossy wireless networks that guarantees a trade-off between loss resilience and short delay based on a rate-distortion optimized scheduling of the video frames, that we also extended to the case of interactive multi-view streaming; a distributed social caching system that, using network coding in conjunction with the knowledge of the users' preferences in terms of views, is able to select a replication scheme such that to provide a high video quality by accessing only other members of the social group without incurring the access cost associated with a connection to a central server and without exchanging large tables of metadata to keep track of the replicated parts; and, finally, a study on using blind source separation techniques to reduce the overhead incurred by network coding schemes based on error-detecting techniques such as parity coding and message digest generation. All our contributions are aimed at using network coding to enhance the quality of video transmission in terms of distortion and delay perceivedLe codage réseau est un paradigme qui permet une utilisation efficace du réseau. Il maximise le débit dans un réseau multi-saut en multicast et réduit le retard. Dans cette thèse, nous concentrons notre attention sur l’intégration du codage réseau aux applications multimédias, et en particulier aux systèmes avancès qui fournissent un service vidéo amélioré pour les utilisateurs. Nos contributions concernent plusieurs scénarios : un cadre de fonctions efficace pour la transmission de flux en directe qui utilise à la fois le codage réseau et le codage par description multiple, une nouvelle stratégie de transmission pour les réseaux sans fil avec perte qui garantit un compromis entre la résilience vis-à-vis des perte et la reduction du retard sur la base d’une optimisation débit-distorsion de l'ordonnancement des images vidéo, que nous avons également étendu au cas du streaming multi-vue interactive, un système replication sociale distribuée qui, en utilisant le réseau codage en relation et la connaissance des préférences des utilisateurs en termes de vue, est en mesure de sélectionner un schéma de réplication capable de fournir une vidéo de haute qualité en accédant seulement aux autres membres du groupe social, sans encourir le coût d’accès associé à une connexion à un serveur central et sans échanger des larges tables de métadonnées pour tenir trace des éléments répliqués, et, finalement, une étude sur l’utilisation de techniques de séparation aveugle de source -pour réduire l’overhead encouru par les schémas de codage réseau- basé sur des techniques de détection d’erreur telles que le codage de parité et la génération de message digest

    Methods for Light Field Display Profiling and Scalable Super-Multiview Video Coding

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    Light field 3D displays reproduce the light field of real or synthetic scenes, as observed by multiple viewers, without the necessity of wearing 3D glasses. Reproducing light fields is a technically challenging task in terms of optical setup, content creation, distributed rendering, among others; however, the impressive visual quality of hologramlike scenes, in full color, with real-time frame rates, and over a very wide field of view justifies the complexity involved. Seeing objects popping far out from the screen plane without glasses impresses even those viewers who have experienced other 3D displays before.Content for these displays can either be synthetic or real. The creation of synthetic (rendered) content is relatively well understood and used in practice. Depending on the technique used, rendering has its own complexities, quite similar to the complexity of rendering techniques for 2D displays. While rendering can be used in many use-cases, the holy grail of all 3D display technologies is to become the future 3DTVs, ending up in each living room and showing realistic 3D content without glasses. Capturing, transmitting, and rendering live scenes as light fields is extremely challenging, and it is necessary if we are about to experience light field 3D television showing real people and natural scenes, or realistic 3D video conferencing with real eye-contact.In order to provide the required realism, light field displays aim to provide a wide field of view (up to 180°), while reproducing up to ~80 MPixels nowadays. Building gigapixel light field displays is realistic in the next few years. Likewise, capturing live light fields involves using many synchronized cameras that cover the same display wide field of view and provide the same high pixel count. Therefore, light field capture and content creation has to be well optimized with respect to the targeted display technologies. Two major challenges in this process are addressed in this dissertation.The first challenge is how to characterize the display in terms of its capabilities to create light fields, that is how to profile the display in question. In clearer terms this boils down to finding the equivalent spatial resolution, which is similar to the screen resolution of 2D displays, and angular resolution, which describes the smallest angle, the color of which the display can control individually. Light field is formalized as 4D approximation of the plenoptic function in terms of geometrical optics through spatiallylocalized and angularly-directed light rays in the so-called ray space. Plenoptic Sampling Theory provides the required conditions to sample and reconstruct light fields. Subsequently, light field displays can be characterized in the Fourier domain by the effective display bandwidth they support. In the thesis, a methodology for displayspecific light field analysis is proposed. It regards the display as a signal processing channel and analyses it as such in spectral domain. As a result, one is able to derive the display throughput (i.e. the display bandwidth) and, subsequently, the optimal camera configuration to efficiently capture and filter light fields before displaying them.While the geometrical topology of optical light sources in projection-based light field displays can be used to theoretically derive display bandwidth, and its spatial and angular resolution, in many cases this topology is not available to the user. Furthermore, there are many implementation details which cause the display to deviate from its theoretical model. In such cases, profiling light field displays in terms of spatial and angular resolution has to be done by measurements. Measurement methods that involve the display showing specific test patterns, which are then captured by a single static or moving camera, are proposed in the thesis. Determining the effective spatial and angular resolution of a light field display is then based on an automated analysis of the captured images, as they are reproduced by the display, in the frequency domain. The analysis reveals the empirical limits of the display in terms of pass-band both in the spatial and angular dimension. Furthermore, the spatial resolution measurements are validated by subjective tests confirming that the results are in line with the smallest features human observers can perceive on the same display. The resolution values obtained can be used to design the optimal capture setup for the display in question.The second challenge is related with the massive number of views and pixels captured that have to be transmitted to the display. It clearly requires effective and efficient compression techniques to fit in the bandwidth available, as an uncompressed representation of such a super-multiview video could easily consume ~20 gigabits per second with today’s displays. Due to the high number of light rays to be captured, transmitted and rendered, distributed systems are necessary for both capturing and rendering the light field. During the first attempts to implement real-time light field capturing, transmission and rendering using a brute force approach, limitations became apparent. Still, due to the best possible image quality achievable with dense multi-camera light field capturing and light ray interpolation, this approach was chosen as the basis of further work, despite the massive amount of bandwidth needed. Decompression of all camera images in all rendering nodes, however, is prohibitively time consuming and is not scalable. After analyzing the light field interpolation process and the data-access patterns typical in a distributed light field rendering system, an approach to reduce the amount of data required in the rendering nodes has been proposed. This approach, on the other hand, requires rectangular parts (typically vertical bars in case of a Horizontal Parallax Only light field display) of the captured images to be available in the rendering nodes, which might be exploited to reduce the time spent with decompression of video streams. However, partial decoding is not readily supported by common image / video codecs. In the thesis, approaches aimed at achieving partial decoding are proposed for H.264, HEVC, JPEG and JPEG2000 and the results are compared.The results of the thesis on display profiling facilitate the design of optimal camera setups for capturing scenes to be reproduced on 3D light field displays. The developed super-multiview content encoding also facilitates light field rendering in real-time. This makes live light field transmission and real-time teleconferencing possible in a scalable way, using any number of cameras, and at the spatial and angular resolution the display actually needs for achieving a compelling visual experience

    Scalable crowd-sourcing of video from mobile devices

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    Contribution To Signalling Of 3d Video Streams In Communication Systems Using The Session Initiation Protocol

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    Las tecnologías de vídeo en 3D han estado al alza en los últimos años, con abundantes avances en investigación unidos a una adopción generalizada por parte de la industria del cine, y una importancia creciente en la electrónica de consumo. Relacionado con esto, está el concepto de vídeo multivista, que abarca el vídeo 3D, y puede definirse como un flujo de vídeo compuesto de dos o más vistas. El vídeo multivista permite prestaciones avanzadas de vídeo, como el vídeo estereoscópico, el “free viewpoint video”, contacto visual mejorado mediante vistas virtuales, o entornos virtuales compartidos. El propósito de esta tesis es salvar un obstáculo considerable de cara al uso de vídeo multivista en sistemas de comunicación: la falta de soporte para esta tecnología por parte de los protocolos de señalización existentes, que hace imposible configurar una sesión con vídeo multivista mediante mecanismos estándar. Así pues, nuestro principal objetivo es la extensión del Protocolo de Inicio de Sesión (SIP) para soportar la negociación de sesiones multimedia con flujos de vídeo multivista. Nuestro trabajo se puede resumir en tres contribuciones principales. En primer lugar, hemos definido una extensión de señalización para configurar sesiones SIP con vídeo 3D. Esta extensión modifica el Protocolo de Descripción de Sesión (SDP) para introducir un nuevo atributo de nivel de medios, y un nuevo tipo de dependencia de descodificación, que contribuyen a describir los formatos de vídeo 3D que pueden emplearse en una sesión, así como la relación entre los flujos de vídeo que componen un flujo de vídeo 3D. La segunda contribución consiste en una extensión a SIP para manejar la señalización de videoconferencias con flujos de vídeo multivista. Se definen dos nuevos paquetes de eventos SIP para describir las capacidades y topología de los terminales de conferencia, por un lado, y la configuración espacial y mapeo de flujos de una conferencia, por el otro. También se describe un mecanismo para integrar el intercambio de esta información en el proceso de inicio de una conferencia SIP. Como tercera y última contribución, introducimos el concepto de espacio virtual de una conferencia, o un sistema de coordenadas que incluye todos los objetos relevantes de la conferencia (como dispositivos de captura, pantallas, y usuarios). Explicamos cómo el espacio virtual se relaciona con prestaciones de conferencia como el contacto visual, la escala de vídeo y la fidelidad espacial, y proporcionamos reglas para determinar las prestaciones de una conferencia a partir del análisis de su espacio virtual, y para generar espacios virtuales durante la configuración de conferencias

    Learning Representations of Social Media Users

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    User representations are routinely used in recommendation systems by platform developers, targeted advertisements by marketers, and by public policy researchers to gauge public opinion across demographic groups. Computer scientists consider the problem of inferring user representations more abstractly; how does one extract a stable user representation - effective for many downstream tasks - from a medium as noisy and complicated as social media? The quality of a user representation is ultimately task-dependent (e.g. does it improve classifier performance, make more accurate recommendations in a recommendation system) but there are proxies that are less sensitive to the specific task. Is the representation predictive of latent properties such as a person's demographic features, socioeconomic class, or mental health state? Is it predictive of the user's future behavior? In this thesis, we begin by showing how user representations can be learned from multiple types of user behavior on social media. We apply several extensions of generalized canonical correlation analysis to learn these representations and evaluate them at three tasks: predicting future hashtag mentions, friending behavior, and demographic features. We then show how user features can be employed as distant supervision to improve topic model fit. Finally, we show how user features can be integrated into and improve existing classifiers in the multitask learning framework. We treat user representations - ground truth gender and mental health features - as auxiliary tasks to improve mental health state prediction. We also use distributed user representations learned in the first chapter to improve tweet-level stance classifiers, showing that distant user information can inform classification tasks at the granularity of a single message.Comment: PhD thesi
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