3D coding tools final report

Livrable D4.3 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D4.3 du projet. Son titre : 3D coding tools final repor

Steered mixture-of-experts for light field images and video : representation and coding

Research in light field (LF) processing has heavily increased over the last decade. This is largely driven by the desire to achieve the same level of immersion and navigational freedom for camera-captured scenes as it is currently available for CGI content. Standardization organizations such as MPEG and JPEG continue to follow conventional coding paradigms in which viewpoints are discretely represented on 2-D regular grids. These grids are then further decorrelated through hybrid DPCM/transform techniques. However, these 2-D regular grids are less suited for high-dimensional data, such as LFs. We propose a novel coding framework for higher-dimensional image modalities, called Steered Mixture-of-Experts (SMoE). Coherent areas in the higher-dimensional space are represented by single higher-dimensional entities, called kernels. These kernels hold spatially localized information about light rays at any angle arriving at a certain region. The global model consists thus of a set of kernels which define a continuous approximation of the underlying plenoptic function. We introduce the theory of SMoE and illustrate its application for 2-D images, 4-D LF images, and 5-D LF video. We also propose an efficient coding strategy to convert the model parameters into a bitstream. Even without provisions for high-frequency information, the proposed method performs comparable to the state of the art for low-to-mid range bitrates with respect to subjective visual quality of 4-D LF images. In case of 5-D LF video, we observe superior decorrelation and coding performance with coding gains of a factor of 4x in bitrate for the same quality. At least equally important is the fact that our method inherently has desired functionality for LF rendering which is lacking in other state-of-the-art techniques: (1) full zero-delay random access, (2) light-weight pixel-parallel view reconstruction, and (3) intrinsic view interpolation and super-resolution

Dense light field coding: a survey

Light Field (LF) imaging is a promising solution for providing more immersive and closer to reality multimedia experiences to end-users with unprecedented creative freedom and flexibility for applications in different areas, such as virtual and augmented reality. Due to the recent technological advances in optics, sensor manufacturing and available transmission bandwidth, as well as the investment of many tech giants in this area, it is expected that soon many LF transmission systems will be available to both consumers and professionals. Recognizing this, novel standardization initiatives have recently emerged in both the Joint Photographic Experts Group (JPEG) and the Moving Picture Experts Group (MPEG), triggering the discussion on the deployment of LF coding solutions to efficiently handle the massive amount of data involved in such systems. Since then, the topic of LF content coding has become a booming research area, attracting the attention of many researchers worldwide. In this context, this paper provides a comprehensive survey of the most relevant LF coding solutions proposed in the literature, focusing on angularly dense LFs. Special attention is placed on a thorough description of the different LF coding methods and on the main concepts related to this relevant area. Moreover, comprehensive insights are presented into open research challenges and future research directions for LF coding.info:eu-repo/semantics/publishedVersio

Scalable light field representation and coding

This Thesis aims to advance the state-of-the-art in light field representation and coding. In this context, proposals to improve functionalities like light field random access and scalability are also presented. As the light field representation constrains the coding approach to be used, several light field coding techniques to exploit the inherent characteristics of the most popular types of light field representations are proposed and studied, which are normally based on micro-images or sub-aperture-images. To encode micro-images, two solutions are proposed, aiming to exploit the redundancy between neighboring micro-images using a high order prediction model, where the model parameters are either explicitly transmitted or inferred at the decoder, respectively. In both cases, the proposed solutions are able to outperform low order prediction solutions. To encode sub-aperture-images, an HEVC-based solution that exploits their inherent intra and inter redundancies is proposed. In this case, the light field image is encoded as a pseudo video sequence, where the scanning order is signaled, allowing the encoder and decoder to optimize the reference picture lists to improve coding efficiency. A novel hybrid light field representation coding approach is also proposed, by exploiting the combined use of both micro-image and sub-aperture-image representation types, instead of using each representation individually. In order to aid the fast deployment of the light field technology, this Thesis also proposes scalable coding and representation approaches that enable adequate compatibility with legacy displays (e.g., 2D, stereoscopic or multiview) and with future light field displays, while maintaining high coding efficiency. Additionally, viewpoint random access, allowing to improve the light field navigation and to reduce the decoding delay, is also enabled with a flexible trade-off between coding efficiency and viewpoint random access.Esta Tese tem como objetivo avançar o estado da arte em representação e codificação de campos de luz. Neste contexto, são também apresentadas propostas para melhorar funcionalidades como o acesso aleatório ao campo de luz e a escalabilidade. Como a representação do campo de luz limita a abordagem de codificação a ser utilizada, são propostas e estudadas várias técnicas de codificação de campos de luz para explorar as características inerentes aos seus tipos mais populares de representação, que são normalmente baseadas em micro-imagens ou imagens de sub-abertura. Para codificar as micro-imagens, são propostas duas soluções, visando explorar a redundância entre micro-imagens vizinhas utilizando um modelo de predição de alta ordem, onde os parâmetros do modelo são explicitamente transmitidos ou inferidos no decodificador, respetivamente. Em ambos os casos, as soluções propostas são capazes de superar as soluções de predição de baixa ordem. Para codificar imagens de sub-abertura, é proposta uma solução baseada em HEVC que explora a inerente redundância intra e inter deste tipo de imagens. Neste caso, a imagem do campo de luz é codificada como uma pseudo-sequência de vídeo, onde a ordem de varrimento é sinalizada, permitindo ao codificador e decodificador otimizar as listas de imagens de referência para melhorar a eficiência da codificação. Também é proposta uma nova abordagem de codificação baseada na representação híbrida do campo de luz, explorando o uso combinado dos tipos de representação de micro-imagem e sub-imagem, em vez de usar cada representação individualmente. A fim de facilitar a rápida implantação da tecnologia de campo de luz, esta Tese também propõe abordagens escaláveis de codificação e representação que permitem uma compatibilidade adequada com monitores tradicionais (e.g., 2D, estereoscópicos ou multivista) e com futuros monitores de campo de luz, mantendo ao mesmo tempo uma alta eficiência de codificação. Além disso, o acesso aleatório de pontos de vista, permitindo melhorar a navegação no campo de luz e reduzir o atraso na descodificação, também é permitido com um equilíbrio flexível entre eficiência de codificação e acesso aleatório de pontos de vista

Livrable D5.2 of the PERSEE project : 2D/3D Codec architecture

Livrable D5.2 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D5.2 du projet. Son titre : 2D/3D Codec architectur

Low Complexity Multiview Video Coding

3D video is a technology that has seen a tremendous attention in the recent years. Multiview Video Coding (MVC) is an extension of the popular H.264 video coding standard and is commonly used to compress 3D videos. It offers an improvement of 20% to 50% in compression efficiency over simulcast encoding of multiview videos using the conventional H.264 video coding standard. However, there are two important problems associated with it: (i) its superior compression performance comes at the cost of significantly higher computational complexity which hampers the real-world realization of MVC encoder in applications such as 3D live broadcasting and interactive Free Viewpoint Television (FTV), and (ii) compressed 3D videos can suffer from packet loss during transmission, which can degrade the viewing quality of the 3D video at the decoder. This thesis aims to solve these problems by presenting techniques to reduce the computational complexity of the MVC encoder and by proposing a consistent error concealment technique for frame losses in 3D video transmission. The thesis first analyses the complexity of the MVC encoder. It then proposes two novel techniques to reduce the complexity of motion and disparity estimation. The first method achieves complexity reduction in the disparity estimation process by exploiting the relationship between temporal levels, type of macroblocks and search ranges while the second method achieves it by exploiting the geometrical relation- ship between motion and disparity vectors in stereo frames. These two methods are then combined with other state-of-the-art methods in a unique framework where gains add up. Experimental results show that the proposed low-complexity framework can reduce the encoding time of the standard MVC encoder by over 93% while maintaining similar compression efficiency performance. The addition of new View Synthesis Prediction (VSP) modes to the MVC encoding framework improves the compression efficiency of MVC. However, testing additional modes comes at the cost of increased encoding complexity. In order to reduce the encoding complexity, the thesis, next, proposes a bayesian early mode decision technique for a VSP enhanced MVC coder. It exploits the statistical similarities between the RD costs of the VSP SKIP mode in neighbouring views to terminate the mode decision process early. Results indicate that the proposed technique can reduce the encoding time of the enhanced MVC coder by over 33% at similar compression efficiency levels. Finally, compressed 3D videos are usually required to be broadcast to a large number of users where transmission errors can lead to frame losses which can degrade the video quality at the decoder. A simple reconstruction of the lost frames can lead to inconsistent reconstruction of the 3D scene which may negatively affect the viewing experience of a user. In order to solve this problem, the thesis proposes, at the end, a consistency model for recovering frames lost during transmission. The proposed consistency model is used to evaluate inter-view and temporal consistencies while selecting candidate blocks for concealment. Experimental results show that the proposed technique is able to recover the lost frames with high consistency and better quality than two standard error concealment methods and a baseline technique based on the boundary matching algorithm

Encoder-Driven Inpainting Strategy in Multiview Video Compression

In free viewpoint video systems, where a user has the freedom to select a virtual view from which an observation image of the 3D scene is rendered, the scene is commonly represented by texture and depth images from multiple nearby viewpoints. In such representation, there exists data redundancy across multiple dimensions: a single visible 3D voxel may be represented by pixels in multiple viewpoint images (inter-view redundancy), a pixel patch may recur in a distant spatial region of the same image due to self-similarity (inter-patch redundancy), and pixels in a local spatial region tend to be similar (inter-pixel redundancy). It isimportant to exploit these redundancies for effective multiview video compression. Existing schemes attempt to eliminate them via the traditional video coding paradigm of hybrid signal prediction/residual coding; typically, the encoder codes explicit information to guide the decoder to the location of the most similar block along with the signal differential. In this paper, we argue that, given the inherent redundancy in the representation, the decoder can often independently recover missing data via inpainting without explicit directions from encoder, resulting in lower coding overhead. Specifically, after pixels in a reference view are projected to a target view via depth image-based rendering (DIBR) at the decoder, the remaining holes in the target view are filled via an inpainting process in a block-by-block manner. First, blocks are ordered in terms of difficulty-to-inpaint by the decoder. Then, explicit instructions are only sent for the reconstruction of the most difficult blocks. In particular, the missing pixels are explicitly coded via a graph Fourier transform (GFT) or a sparsification procedure using DCT, which leads to low coding cost. For the blocks that are easy to inpaint, the decoder independently completes missing pixels via template-based inpainting. We implemented our encoder-driven inpainting strategy as an extension of High Efficiency Video Coding (HEVC). Experimental results show that our coding strategy can outperform comparable implementation of HEVC by up to 0.8dB in reconstructed image qualit

Light field image compression

Light field imaging based on a single-tier camera equipped with a micro-lens array has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require identifying adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, this chapter presents some of the most recent light field image coding solutions that have been investigated. After a brief review of the current state of the art in image coding formats for light field photography, an experimental study of the rate-distortion performance for different coding formats and architectures is presented. Then, aiming at enabling faster deployment of light field applications and services in the consumer market, a scalable light field coding solution that provides backward compatibility with legacy display devices (e.g., 2D, 3D stereo, and 3D multiview) is also presented. Furthermore, a light field coding scheme based on a sparse set of microimages and the associated blockwise disparity is also presented. This coding scheme is scalable with three layers such that the rendering can be performed with the sparse micro-image set, the reconstructed light field image, and the decoded light field image.info:eu-repo/semantics/acceptedVersio