53 research outputs found

    MediaSync: Handbook on Multimedia Synchronization

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    This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

    Media gateway utilizando um GPU

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    Mestrado em Engenharia de Computadores e Telemátic

    Robust density modelling using the student's t-distribution for human action recognition

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    The extraction of human features from videos is often inaccurate and prone to outliers. Such outliers can severely affect density modelling when the Gaussian distribution is used as the model since it is highly sensitive to outliers. The Gaussian distribution is also often used as base component of graphical models for recognising human actions in the videos (hidden Markov model and others) and the presence of outliers can significantly affect the recognition accuracy. In contrast, the Student's t-distribution is more robust to outliers and can be exploited to improve the recognition rate in the presence of abnormal data. In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement in classification accuracy. © 2011 IEEE

    Object Duplicate Detection

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    With the technological evolution of digital acquisition and storage technologies, millions of images and video sequences are captured every day and shared in online services. One way of exploring this huge volume of images and videos is through searching a particular object depicted in images or videos by making use of object duplicate detection. Therefore, need of research on object duplicate detection is validated by several image and video retrieval applications, such as tag propagation, augmented reality, surveillance, mobile visual search, and television statistic measurement. Object duplicate detection is detecting visually same or very similar object to a query. Input is not restricted to an image, it can be several images from an object or even it can be a video. This dissertation describes the author's contribution to solve problems on object duplicate detection in computer vision. A novel graph-based approach is introduced for 2D and 3D object duplicate detection in still images. Graph model is used to represent the 3D spatial information of the object based on the local features extracted from training images so that an explicit and complex 3D object modeling is avoided. Therefore, improved performance can be achieved in comparison to existing methods in terms of both robustness and computational complexity. Our method is shown to be robust in detecting the same objects even when images containing the objects are taken from very different viewpoints or distances. Furthermore, we apply our object duplicate detection method to video, where the training images are added iteratively to the video sequence in order to compensate for 3D view variations, illumination changes and partial occlusions. Finally, we show several mobile applications for object duplicate detection, such as object recognition based museum guide, money recognition or flower recognition. General object duplicate detection may fail to detection chess figures, however considering context, like chess board position and height of the chess figure, detection can be more accurate. We show that user interaction further improves image retrieval compared to pure content-based methods through a game, called Epitome

    Radio Resource Management Optimization For Next Generation Wireless Networks

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    The prominent versatility of today’s mobile broadband services and the rapid advancements in the cellular phones industry have led to a tremendous expansion in the wireless market volume. Despite the continuous progress in the radio-access technologies to cope with that expansion, many challenges still remain that need to be addressed by both the research and industrial sectors. One of the many remaining challenges is the efficient allocation and management of wireless network resources when using the latest cellular radio technologies (e.g., 4G). The importance of the problem stems from the scarcity of the wireless spectral resources, the large number of users sharing these resources, the dynamic behavior of generated traffic, and the stochastic nature of wireless channels. These limitations are further tightened as the provider’s commitment to high quality-of-service (QoS) levels especially data rate, delay and delay jitter besides the system’s spectral and energy efficiencies. In this dissertation, we strive to solve this problem by presenting novel cross-layer resource allocation schemes to address the efficient utilization of available resources versus QoS challenges using various optimization techniques. The main objective of this dissertation is to propose a new predictive resource allocation methodology using an agile ray tracing (RT) channel prediction approach. It is divided into two parts. The first part deals with the theoretical and implementational aspects of the ray tracing prediction model, and its validation. In the second part, a novel RT-based scheduling system within the evolving cloud radio access network (C-RAN) architecture is proposed. The impact of the proposed model on addressing the long term evolution (LTE) network limitations is then rigorously investigated in the form of optimization problems. The main contributions of this dissertation encompass the design of several heuristic solutions based on our novel RT-based scheduling model, developed to meet the aforementioned objectives while considering the co-existing limitations in the context of LTE networks. Both analytical and numerical methods are used within this thesis framework. Theoretical results are validated with numerical simulations. The obtained results demonstrate the effectiveness of our proposed solutions to meet the objectives subject to limitations and constraints compared to other published works

    Etude et mise en place d’une plateforme d’adaptation multiservice embarquée pour la gestion de flux multimédia à différents niveaux logiciels et matériels

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    On the one hand, technology advances have led to the expansion of the handheld devices market. Thanks to this expansion, people are more and more connected and more and more data are exchanged over the Internet. On the other hand, this huge amound of data imposes drastic constrains in order to achieve sufficient quality. The Internet is now showing its limits to assure such quality. To answer nowadays limitations, a next generation Internet is envisioned. This new network takes into account the content nature (video, audio, ...) and the context (network state, terminal capabilities ...) to better manage its own resources. To this extend, video manipulation is one of the key concept that is highlighted in this arising context. Video content is more and more consumed and at the same time requires more and more resources. Adapting videos to the network state (reducing its bitrate to match available bandwidth) or to the terminal capabilities (screen size, supported codecs, …) appears mandatory and is foreseen to take place in real time in networking devices such as home gateways. However, video adaptation is a resource intensive task and must be implemented using hardware accelerators to meet the desired low cost and real time constraints.In this thesis, content- and context-awareness is first analyzed to be considered at the network side. Secondly, a generic low cost video adaptation system is proposed and compared to existing solutions as a trade-off between system complexity and quality. Then, hardware conception is tackled as this system is implemented in an FPGA based architecture. Finally, this system is used to evaluate the indirect effects of video adaptation; energy consumption reduction is achieved at the terminal side by reducing video characteristics thus permitting an increased user experience for End-Users.Les avancées technologiques ont permis la commercialisation à grande échelle de terminaux mobiles. De ce fait, l’homme est de plus en plus connecté et partout. Ce nombre grandissant d’usagers du réseau ainsi que la forte croissance du contenu disponible, aussi bien d’un point de vue quantitatif que qualitatif saturent les réseaux et l’augmentation des moyens matériels (passage à la fibre optique) ne suffisent pas. Pour surmonter cela, les réseaux doivent prendre en compte le type de contenu (texte, vidéo, ...) ainsi que le contexte d’utilisation (état du réseau, capacité du terminal, ...) pour assurer une qualité d’expérience optimum. A ce sujet, la vidéo fait partie des contenus les plus critiques. Ce type de contenu est non seulement de plus en plus consommé par les utilisateurs mais est aussi l’un des plus contraignant en terme de ressources nécéssaires à sa distribution (taille serveur, bande passante, …). Adapter un contenu vidéo en fonction de l’état du réseau (ajuster son débit binaire à la bande passante) ou des capacités du terminal (s’assurer que le codec soit nativement supporté) est indispensable. Néanmoins, l’adaptation vidéo est un processus qui nécéssite beaucoup de ressources. Cela est antinomique à son utilisation à grande echelle dans les appareils à bas coûts qui constituent aujourd’hui une grande part dans l’ossature du réseau Internet. Cette thèse se concentre sur la conception d’un système d’adaptation vidéo à bas coût et temps réel qui prendrait place dans ces réseaux du futur. Après une analyse du contexte, un système d’adaptation générique est proposé et évalué en comparaison de l’état de l’art. Ce système est implémenté sur un FPGA afin d’assurer les performances (temps-réels) et la nécessité d’une solution à bas coût. Enfin, une étude sur les effets indirects de l’adaptation vidéo est menée

    Etude et mise en place d'une plateforme d'adaptation multiservice embarquée pour la gestion de flux multimédia à différents niveaux logiciels et matériels

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    Les avancées technologiques ont permis la commercialisation à grande échelle de terminaux mobiles. De ce fait, l homme est de plus en plus connecté et partout. Ce nombre grandissant d usagers du réseau ainsi que la forte croissance du contenu disponible, aussi bien d un point de vue quantitatif que qualitatif saturent les réseaux et l augmentation des moyens matériels (passage à la fibre optique) ne suffisent pas. Pour surmonter cela, les réseaux doivent prendre en compte le type de contenu (texte, vidéo, ...) ainsi que le contexte d utilisation (état du réseau, capacité du terminal, ...) pour assurer une qualité d expérience optimum. A ce sujet, la vidéo fait partie des contenus les plus critiques. Ce type de contenu est non seulement de plus en plus consommé par les utilisateurs mais est aussi l un des plus contraignant en terme de ressources nécéssaires à sa distribution (taille serveur, bande passante, ). Adapter un contenu vidéo en fonction de l état du réseau (ajuster son débit binaire à la bande passante) ou des capacités du terminal (s assurer que le codec soit nativement supporté) est indispensable. Néanmoins, l adaptation vidéo est un processus qui nécéssite beaucoup de ressources. Cela est antinomique à son utilisation à grande echelle dans les appareils à bas coûts qui constituent aujourd hui une grande part dans l ossature du réseau Internet. Cette thèse se concentre sur la conception d un système d adaptation vidéo à bas coût et temps réel qui prendrait place dans ces réseaux du futur. Après une analyse du contexte, un système d adaptation générique est proposé et évalué en comparaison de l état de l art. Ce système est implémenté sur un FPGA afin d assurer les performances (temps-réels) et la nécessité d une solution à bas coût. Enfin, une étude sur les effets indirects de l adaptation vidéo est menée.On the one hand, technology advances have led to the expansion of the handheld devices market. Thanks to this expansion, people are more and more connected and more and more data are exchanged over the Internet. On the other hand, this huge amound of data imposes drastic constrains in order to achieve sufficient quality. The Internet is now showing its limits to assure such quality. To answer nowadays limitations, a next generation Internet is envisioned. This new network takes into account the content nature (video, audio, ...) and the context (network state, terminal capabilities ...) to better manage its own resources. To this extend, video manipulation is one of the key concept that is highlighted in this arising context. Video content is more and more consumed and at the same time requires more and more resources. Adapting videos to the network state (reducing its bitrate to match available bandwidth) or to the terminal capabilities (screen size, supported codecs, ) appears mandatory and is foreseen to take place in real time in networking devices such as home gateways. However, video adaptation is a resource intensive task and must be implemented using hardware accelerators to meet the desired low cost and real time constraints.In this thesis, content- and context-awareness is first analyzed to be considered at the network side. Secondly, a generic low cost video adaptation system is proposed and compared to existing solutions as a trade-off between system complexity and quality. Then, hardware conception is tackled as this system is implemented in an FPGA based architecture. Finally, this system is used to evaluate the indirect effects of video adaptation; energy consumption reduction is achieved at the terminal side by reducing video characteristics thus permitting an increased user experience for End-Users.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

    Resource-Constrained Low-Complexity Video Coding for Wireless Transmission

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