by tmaugey

[Sep 19] New journal article accepted in Physical Communication

Title: Rate-Storage Regions for Extractable Source Coding with Side Information

Authors: E. Dupraz, T. Maugey, A. Roumy, M. Kieffer

Abstract:This papers considers the coding of a source with decoders, each having access to a different side information . We define a new source coding problem called Extractable Source Coding with Side Information (ESC-SI). In this problem, the server stores one single coded description of the source, from which descriptions can be extracted without re-encoding, depending on the side information available at the decoder. We want to minimize both the storage rate of the source on the server, and the transmission rates from the server to the decoders. We provide the achievable storage-transmission rate regions for lossless source coding of general, non i.i.d., non-ergodic sources, and the achievable storage-transmission rate–distortion regions for lossy source coding for non i.i.d. Gaussian sources. The regions obtained for such general source models provide insightful design guidelines for practical applications.

by tmaugey

[Aug 19] three papers accepted at PCS 2019

The three following papers are accepted and will be presented at the Picture Coding Symposium (PCS) 2019, in China:

N. Mahmoudian Bidgoli, T. Maugey , A. Roumy, Intra-coding of 360-degree images on the sphere
Picture Coding Symposium (PCS), Ningbo, China, Nov. 2019

N. Mahmoudian Bidgoli, T. Maugey, A. Roumy, F. Nasiri and F. Payan, A geometry-aware compression of 3D mesh texture with random access
Picture Coding Symposium (PCS), Ningbo, China, Nov. 2019

P. Garus, J. Jung, T. Maugey and C. Guillemot, Bypassing Depth Maps Transmission For Immersive Video Coding
Picture Coding Symposium (PCS), Ningbo, China, Nov. 2019

by tmaugey

[June 19] New journal article accepted in IEEE TIP

Title: Geometry-Aware Graph Transforms for Light Field Compact Representation

Authors: Mira Rizkallah, Xin Su, Thomas Maugey, Christine Guillemot

Abstract: The paper addresses the problem of energy compaction of dense 4D light fields by designing geometry-aware local graph-based transforms. Local graphs are constructed on super-rays that can be seen as a grouping of spatially and geometry-dependent angularly correlated pixels. Both non separable and separable transforms are considered. Despite the local support of limited size defined by the super-rays, the Laplacian matrix of the non separable graph remains of high dimension and its diagonalization to compute the transform eigen vectors remains computationally expensive. To solve this problem, we then perform the local spatio-angular transform in a separable manner. We show that when the shape of corresponding super-pixels in the different views is not isometric, the basis
functions of the spatial transforms are not coherent, resulting in decreased correlation between spatial transform coefficients. We hence propose a novel transform optimization method that aims at preserving angular correlation even when the shapes of the super-pixels are not isometric. Experimental results show the benefit of the approach in terms of energy compaction. A coding scheme is also described to assess the rate-distortion perfomances of the proposed transforms and is compared to state of the art
encoders namely HEVC-lozenge [1], JPEG pleno 1.1 [2], HEVC- pseudo [3] and HLRA [4] .

by tmaugey

[May 2019] One paper accepted in ICIP

Title: Evaluation framework for 360-degree visual content compression with user-dependent transmission

Authors: Navid MAHMOUDIAN BIDGOLI, Thomas MAUGEY, Aline ROUMY

Abstract: Immersive visual experience can be obtained by allowing the user to navigate in a 360-degree visual content. These contents are stored in high resolution and need a lot of space on the server to store them. The transmission depends on the user’s request and only the spatial region which is requested by the user is transmitted to avoid wasting network bandwidth. Therefore, storage and transmission rates are both critical.
%The former is important to reduce the space for storage on the server and the latter reduces the bitrate for the available network bandwidth.
Splitting the rates into storage and transmission has not been formally considered in the literature for evaluating 360-degree content compression algorithms. In this paper, we propose a framework to evaluate the coding efficiency of 360-degree content while discriminating between storage and transmission rate and taking into account user dependency. This brings the flexibility to compare different coding methods based on the storage capacity on the server and network bandwidth of users.

by tmaugey

[Apr 2019] New paper accepted in ACM Multimedia System conference

Title: FTV360: a Multiview 360° Video Dataset with Calibration Parameters

Authors: Thomas Maugey, Laurent Guillo, Cédric Le Cam

Abstract: In this paper, we present a new dataset in order to serve as a support for researches in Free Viewpoint Television (FTV) and 6 degrees-of-freedom (6DoF) immersive communication. This dataset relies on a novel acquisition procedure consisting in a synchronized capture of a scene by 40 omnidirectional cameras. We have also developed a calibration solution that estimates the position and orientation of each camera with respect to a same reference. This solution relies on a regular calibration of each individual camera, and a graph-based synchronization of all these parameters. These videos and the calibration solution are made publicly available.

by tmaugey

[Feb 2019] One ICASSP paper accepted

Authors: F. Nasiri, N. Mahmoudian-Bigdoli, F. Payan, T. Maugey
Title: A geometry-aware framework for compressing 3D mesh textures, accepted in IEEE ICASSP 2019
Abstract: In this paper, we propose a novel prediction tool for improving the compression performance of texture atlases. This algorithm, called Geometry-Aware (GA) intra coding, takes advantage of the topology of the associated 3D meshes, in order to reduce the redundancies in the texture map. For texture processing, the general concept of the conventional intra prediction, used in video compression, has been adapted to utilize neighboring information on the 3D surface. We have also studied how this prediction tool can be integrated into a complete coding solution. In particular, a new block scanning strategy, as well as a graph-based transform for residual coding have been proposed. Experimental results show that the knowledge of the mesh topology can significantly improve the compression efficiency of texture atlases.

by tmaugey

[Jan 2019] A paper accepted at DCC’19 conference

Authors: Mira Rizkallah, Thomas Maugey, Christine Guillemot
Title: Graph-based Spatio-angular Prediction for Quasi-Lossless Compression of Light Fields, accepted in IEEE DCC 2019
Abstract: Graph-based transforms have been shown to be powerful tools for image compression. However, the computation of the basis functions becomes rapidly untractable when the support increases, i.e. when the dimension of the data is high as in the case of light fields. Local transforms with limited supports have been investigated to cope with this difficulty. Nevertheless, the locality of the support may not allow us to fully exploit long term dependencies in the signal. In this paper, we describe a graph-based prediction solution that allows taking advantage of intra prediction mechanisms as well as of the good energy compaction properties of the graph transform. The approach relies on a separable spatio-angular transform and  derives low frequency spatio-angular coefficients from one single compressed reference view and from the high angular frequency coefficients. In the tests, we used HEVC-Intra, with QP=0, to encode the reference frame with high quality. The high angular frequency coefficients containing very little energy are coded using a simple entropy coder. The approach is shown to be very efficient in a context of high quality quasi-lossless compression of light fields.

by tmaugey

[Oct 2018] Our dataset available

Our dataset for Free Viewpoint Television is now available.

To check the details, download the videos and get our source codes used for the calibration, please visit our website: https://project.inria.fr/ftv360/

 

If you use any material (videos, codes) shared on this website for research purposes, please cite the following paper:

Thomas Maugey, Laurent Guillo, Cédric Le Cam, FTV360: a Multiview 360-degree Video Dataset with Calibration Parameters, ACM Multimedia Systems Conference, June 2019