2,251 research outputs found

    A New Fast Motion Estimation and Mode Decision algorithm for H.264 Depth Maps encoding in Free Viewpoint TV

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    In this paper, we consider a scenario where 3D scenes are modeled through a View+Depth representation. This representation is to be used at the rendering side to generate synthetic views for free viewpoint video. The encoding of both type of data (view and depth) is carried out using two H.264/AVC encoders. In this scenario we address the reduction of the encoding complexity of depth data. Firstly, an analysis of the Mode Decision and Motion Estimation processes has been conducted for both view and depth sequences, in order to capture the correlation between them. Taking advantage of this correlation, we propose a fast mode decision and motion estimation algorithm for the depth encoding. Results show that the proposed algorithm reduces the computational burden with a negligible loss in terms of quality of the rendered synthetic views. Quality measurements have been conducted using the Video Quality Metric

    Reducing the complexity of a multiview H.264/AVC and HEVC hybrid architecture

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    With the advent of 3D displays, an efficient encoder is required to compress the video information needed by them. Moreover, for gradual market acceptance of this new technology, it is advisable to offer backward compatibility with existing devices. Thus, a multiview H.264/Advance Video Coding (AVC) and High Efficiency Video Coding (HEVC) hybrid architecture was proposed in the standardization process of HEVC. However, it requires long encoding times due to the use of HEVC. With the aim of tackling this problem, this paper presents an algorithm that reduces the complexity of this hybrid architecture by reducing the encoding complexity of the HEVC views. By using Na < ve-Bayes classifiers, the proposed technique exploits the information gathered in the encoding of the H.264/AVC view to make decisions on the splitting of coding units in HEVC side views. Given the novelty of the proposal, the only similar work found in the literature is an unoptimized version of the algorithm presented here. Experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity

    Compression vidéo basée sur l'exploitation d'un décodeur intelligent

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    This Ph.D. thesis studies the novel concept of Smart Decoder (SDec) where the decoder is given the ability to simulate the encoder and is able to conduct the R-D competition similarly as in the encoder. The proposed technique aims to reduce the signaling of competing coding modes and parameters. The general SDec coding scheme and several practical applications are proposed, followed by a long-term approach exploiting machine learning concept in video coding. The SDec coding scheme exploits a complex decoder able to reproduce the choice of the encoder based on causal references, eliminating thus the need to signal coding modes and associated parameters. Several practical applications of the general outline of the SDec scheme are tested, using different coding modes during the competition on the reference blocs. Despite the choice for the SDec reference block being still simple and limited, interesting gains are observed. The long-term research presents an innovative method that further makes use of the processing capacity of the decoder. Machine learning techniques are exploited in video coding with the purpose of reducing the signaling overhead. Practical applications are given, using a classifier based on support vector machine to predict coding modes of a block. The block classification uses causal descriptors which consist of different types of histograms. Significant bit rate savings are obtained, which confirms the potential of the approach.Cette thèse de doctorat étudie le nouveau concept de décodeur intelligent (SDec) dans lequel le décodeur est doté de la possibilité de simuler l’encodeur et est capable de mener la compétition R-D de la même manière qu’au niveau de l’encodeur. Cette technique vise à réduire la signalisation des modes et des paramètres de codage en compétition. Le schéma général de codage SDec ainsi que plusieurs applications pratiques sont proposées, suivis d’une approche en amont qui exploite l’apprentissage automatique pour le codage vidéo. Le schéma de codage SDec exploite un décodeur complexe capable de reproduire le choix de l’encodeur calculé sur des blocs de référence causaux, éliminant ainsi la nécessité de signaler les modes de codage et les paramètres associés. Plusieurs applications pratiques du schéma SDec sont testées, en utilisant différents modes de codage lors de la compétition sur les blocs de référence. Malgré un choix encore simple et limité des blocs de référence, les gains intéressants sont observés. La recherche en amont présente une méthode innovante qui permet d’exploiter davantage la capacité de traitement d’un décodeur. Les techniques d’apprentissage automatique sont exploitées pour but de réduire la signalisation. Les applications pratiques sont données, utilisant un classificateur basé sur les machines à vecteurs de support pour prédire les modes de codage d’un bloc. La classification des blocs utilise des descripteurs causaux qui sont formés à partir de différents types d’histogrammes. Des gains significatifs en débit sont obtenus, confirmant ainsi le potentiel de l’approche

    Overview of 3D Video: Coding Algorithms, Implementations and Standardization

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    Projecte final de carrera fet en col.laboració amb Linköping Institute of TechnologyEnglish: 3D technologies have aroused a great interest over the world in the last years. Television, cinema and videogames are introducing, little by little, 3D technologies into the mass market. This comes as a result of the research done in the 3D field, solving many of its limitations such as quality, contents creation or 3D displays. This thesis focus on 3D video, considering concepts that concerns the coding issues and the video formats. The aim is to provide an overview of the current state of 3D video, including the standardization and some interesting implementations and alternatives that exist. In the report necessary background information is presented in order to understand the concepts developed: compression techniques, the different video formats, their standardization and some advances or alternatives to the processes previously explained. Finally, a comparison between the different concepts is presented to complete the overview, ending with some conclusions and proposed ideas for future works.Castellano: Las tecnologías 3D han despertado un gran interés en todo el mundo en los últimos años. Televisión, cine y videojuegos están introduciendo, poco a poco, ésta tecnología en el mercado. Esto es resultado de la investigación realizada en el campo de las 3D, solucionando muchas de sus limitaciones, como la calidad, la creación de contenidos o las pantallas 3D. Este proyecto se centra en el video 3D, considerando los conceptos relacionados con la codificación y los formatos de vídeo. El objetivo es proporcionar una visión del estado actual del vídeo 3D, incluyendo los estándares y algunas de las implementaciones más interesantes que existen. En la memoria, se presenta información adicional para facilitar el seguimiento de los conceptos desarrollados: técnicas de compresión, formatos de vídeo, su estandarización y algunos avances o alternativas a los procesos explicados. Finalmente, se presentan diferentes comparaciones entre los conceptos tratados, acabando el documento con las conclusiones obtenidas e ideas propuestas para futuros trabajos.Català: Les tecnologies 3D han despertat un gran interès a tot el món en els últims anys. Televisió, cinema i videojocs estan introduint, lentament, aquesta tecnologia en el mercat. Això és resultat de la investigació portada a terme en el camp de les 3D, solucionant moltes de les seves limitacions, com la qualitat, la creació de continguts o les pantalles 3D. Aquest proyecte es centra en el video 3D, considerant els conceptes relacionats amb la codificació i els formats de video. L'objectiu és proporcionar una visió de l'estat actual del video 3D, incloent-hi els estandàrds i algunes de les implementacions més interessants que existeixen. A la memòria, es presenta informació adicional per facilitar el seguiment dels conceptes desenvolupats: tècniques de compressió, formats de video, la seva estandardització i alguns avenços o alternatives als procesos explicats. Finalment, es presenten diferents comparacions entre els conceptes tractats i les conclusions obtingudes, juntament amb propostes per a futurs treballs

    Depth map compression via 3D region-based representation

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    In 3D video, view synthesis is used to create new virtual views between encoded camera views. Errors in the coding of the depth maps introduce geometry inconsistencies in synthesized views. In this paper, a new 3D plane representation of the scene is presented which improves the performance of current standard video codecs in the view synthesis domain. Two image segmentation algorithms are proposed for generating a color and depth segmentation. Using both partitions, depth maps are segmented into regions without sharp discontinuities without having to explicitly signal all depth edges. The resulting regions are represented using a planar model in the 3D world scene. This 3D representation allows an efficient encoding while preserving the 3D characteristics of the scene. The 3D planes open up the possibility to code multiview images with a unique representation.Postprint (author's final draft

    A novel view-level target bit rate distribution estimation technique for real-time multi-view video plus depth

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    This paper presents a novel view-level target bit rate distribution estimation technique for real-time Multi-view video plus depth using a statistical model that is based on the prediction mode distribution. Experiments using various standard test sequences show the efficacy of the technique, as the model manages to estimate online the view-level target bit rate distribution with an absolute mean estimation error of 2% and a standard deviation of 0.9%. Moreover, this technique provides adaptation of the view-level bit rate distribution providing scene change handling capability.peer-reviewe
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