Universite Paris 13
Universite Paris 13
Universite Paris 13
Universite Paris 13
Universite Paris 13
Universite Paris 13

Multimedia Group

Topic 1: Quality and Representation of Multimedia Content

Visual Perception Models for Visual Data Analysis and Processing

We develop perceptual models of visual information representation and extraction of descriptors and visual attributes

(contrast, visibility map and visual masking) for processing, analysis and coding of visual information. The first stages

of the humanvisual system are taken into account, in particular multi-resolution and multidirectional contrast, masking

phenomenon as well as multichannel decomposition

Visual information quality

It involves evaluating and/or improving the visual information quality (multimodal medical images, stereoscopic

medical images, HDR images, stereoscopic images, stereoscopic video, endoscopic video, etc.) either

coded/decoded, transmitted (filtering, enhancement of contrast ...). We differentiate ourselves from current trends

by avoiding the development of purely mathematical (PSNR) measures, or completely inspired by the human visual

system for which the number of parameters to be adjusted is quite large.

 Coding with quality control

Source coding mechanisms are developed by integrating distortion level indicators to optimize the quality of visual

information. The degradation effects, which can result from the motion (respectively disparity) estimation stage inthe

video (respectively stereoscopic image) coding, scheme are taken into consideration.


Topic 2: Machine Learning and Multimedia Data Mining

Image processing and machine learning

We are interested in machine learning methods for multimedia content processing. The aim is to develop methods of

processing multimodal medical images (segmentation, denoising, super-resolution ...) based on machine learning.

These methods aim to take into account the characteristics of the human visual system through models whose

parameters are estimated by machine learning methods. We are also interested in estimating the subjective image

quality by statistical learning methods.

Data mining and social networks

The aim is to develop approaches derived from the statistical learning theory for structured data processing (numerical

attributes, texts, multimedia data) resulting from social graphs. We are interested in exploiting the knowledge of the

links between a set of actors to improve the construction of models: to plan, identify and characterize a group of actors.

Network group

Topic 1 : R3D : Wireless Networks ( Dimensionning , Deployment, D issemination )

Dimensionning of wirless networks

Deployment of wireless networks

  • Deploying Sensor Networks
  • Deployment in wireless mesh networks .


  • Geocast VANETs routing in vehicle networks
  • Routing in wireless sensor networks
Topic 2 : RIS Networks  Infrastructure and services
Networks infrastructure
  • Optical Networks / GMPLS
  • Multi-constrained routing in networks

Novel paradigms for networking services

Application-specific topics

  • Support for multiplayer games on wireless Ad Hoc networks  
  •  Architecture ITS for road traffic management 
  •  Dissemination of information in eHealth Wirless environments

Contact & Access

L2TI , Institut Galilée, UP 13
99, avenue Jean-Baptiste Clément
F-93430 Villetaneuse
ico telephone  +33 1 49 40 28 59
ico fax  +33 1 49 40 40 61
ico email  secretariat-l2ti[at]univ-paris13.fr

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