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Lozenguez G.,GREYC | Lozenguez G.,University Blaise Pascal | Adouane L.,University Blaise Pascal | Beynier A.,University Pierre and Marie Curie | And 2 more authors.
Multiagent and Grid Systems | Year: 2012

In this paper, an approach is presented to automatically allocate a set of exploration tasks between a fleet of mobile robots. The approach combines a Road-Map technique and Markovian Decision Processes (MDPs). The addressed problem consists of exploring an area where a set of points of interest characterizes the main positions to be visited by the robots. This problem induces a long term horizon motion planning with a combinatorial explosion. The Road-Map allows the robots to represent their spatial knowledge as a graph of way-points connected by paths. It can be modified during the exploration mission requiring the robots to use on-line computations. By decomposing the Road-Map into regions, an MDP allows the current group leader to evaluate the interest of each robot in every single region. Using those values, the leader can assign the exploration tasks to the robots. © 2012 - IOS Press and the authors. All rights reserved.


Lozenguez G.,GREYC | Lozenguez G.,University Blaise Pascal | Adouane L.,University Blaise Pascal | Beynier A.,University Pierre and Marie Curie | And 2 more authors.
Advances in Intelligent and Soft Computing | Year: 2011

In this paper, we present an approach to automatically allocate a set of exploration tasks between a fleet of mobile robots. Our approach combines a RoadMap technique and Markovian Decision Processes (MDPs).We are interested in the problem of exploring an area where several robots need to visit a set of points of interest. This problem induces a long term horizon motion planning with a combinatorial explosion. The RoadMap allows us to represent spatial knowledge as a graph of paths. It can be modified during the exploration mission requiring the robots to use on-line computation. By decomposing the RoadMap into regions, an MDP allows the leader robot to evaluate the interest of each robot in every single region. Using those values, the leader can assign the exploration tasks to the robots. © 2011 Springer-Verlag Berlin Heidelberg.


Labadie A.,GREYC | Ferrari S.,GREYC | Roy T.,Noopsis
IC3K 2013; KEOD 2013 - 5th International Conference on Knowledge Engineering and Ontology Development, Proceedings | Year: 2013

This paper presents the computational aspects of the SemComp project, a multidisciplinary collaboration aiming at observing how interacting with documents acts on knowledge acquisition. It is based on a model for personalized semantic resources inspired from componential linguistics. The paper describes the advances in both the computational model's definition as well as its implementation in a Web oriented application. Functionalities and technical choices are presented with regards to the expected experiments. Copyright ©2013 SCITEPRESS.


Gama N.,GREYC | Nguyen P.Q.,French Institute for Research in Computer Science and Automation | Regev O.,Tel Aviv University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

Lattice enumeration algorithms are the most basic algorithms for solving hard lattice problems such as the shortest vector problem and the closest vector problem, and are often used in public-key cryptanalysis either as standalone algorithms, or as subroutines in lattice reduction algorithms. Here we revisit these fundamental algorithms and show that surprising exponential speedups can be achieved both in theory and in practice by using a new technique, which we call extreme pruning. We also provide what is arguably the first sound analysis of pruning, which was introduced in the 1990s by Schnorr et al. © 2010 Springer-Verlag.


Bretto A.,GREYC | Bretto A.,Telecom ParisTech | Ducournau A.,ENISE DIPI | Rital S.,Telecom ParisTech
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

In this paper, we introduce a novel hypergraph reduction algorithm, and we evaluate it in an innovative method for joint segmentation and classification of satellite image content. It operates in 3 steps. First, we compute an Image Neighborhood Hypergraph representation (INH). Second, we reduce the INH model and we exploit a morphism from INH to Reduced INH (RINH) to generate superpixels. Then, we perform a superpixels supervised classification according to their features. Our approach is very fast and can deal with great sized images. Its reliability has been tested on several satellite images with comparison to single pixelwise classification. © 2010 Springer-Verlag.


Condat L.,GREYC
IEEE Transactions on Image Processing | Year: 2011

Digital color cameras acquire color images by means of a sensor on which a color filter array (CFA) is overlaid. The Bayer CFA dominates the consumer market, but there has recently been a renewed interest for the design of CFAs . However, robustness to noise is often neglected in the design, though it is crucial in practice. In this paper, we present a new 2 × 3-periodic CFA which provides, by construction, the optimal tradeoff between robustness to aliasing, chrominance noise and luminance noise. Moreover, a simple and efficient linear demosaicking algorithm is described, which fully exploits the spectral properties of the CFA. Practical experiments confirm the superiority of our design, both in noiseless and noisy scenarios. © 2011 IEEE.


Ghoniem M.,GREYC | Chahir Y.,GREYC | Elmoataz A.,GREYC
Signal Processing | Year: 2010

We present nonlocal algorithms for video denoising, simplification and inpainting based on a generic framework of discrete regularization on graphs. We express video denoising, simplification and inpainting problems using the same variational formulation. The main advantage of this framework is the unification of local and nonlocal approaches for these processing procedures. We take advantage of temporal and spatial redundancies in order to produce high quality results. In this paper, we consider a video sequence as a volume rather than a sequence of frames, and employ algorithms that do not require any motion estimation. For video inpainting, we unify geometric- and texture-synthesis-based approaches. To reduce the computational effort, we propose an optimized method that is faster than the nonlocal approach, while producing equally appealing results. © 2009 Elsevier B.V. All rights reserved.


Condat L.,GREYC
Image and Vision Computing | Year: 2010

We propose two new types of random patterns with R, G, B colors, which allow to design color filter arrays (CFAs) with good spectral properties. Indeed, the chrominance channels have blue noise characteristics, a property which maximizes the robustness of the acquisition system to aliasing. With these new CFAs, the demosaicking artifacts appear as incoherent noise, which is less visually disturbing than the moiré structures characteristic of CFAs with periodic patterns. © 2009 Elsevier B.V. All rights reserved.


Renault C.,GREYC | Desvignes M.,GREYC | Revenu M.,GREYC
European Signal Processing Conference | Year: 2015

Automatic labelling and identification of cerebral structure, like cortical sulci, are useful in neurology, surgery planning, etc... We propose a cortical sulci valley detection. The aim of the method is to achieve the sulci medial surface. The method applied on MRI data, is based on geometrical features (curvature) which doesn't require the accurate segmentation of the cerebral cortex. We use a sub-voxel precision tracking. The minimum curvature vector in each point allows successive displacement along the valley of sulci. Partial derivatives provide the differential characteristics. © 2000 EUSIPCO.


PubMed | GREYC
Type: Journal Article | Journal: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society | Year: 2011

Digital color cameras acquire color images by means of a sensor on which a color filter array (CFA) is overlaid. The Bayer CFA dominates the consumer market, but there has recently been a renewed interest for the design of CFAs . However, robustness to noise is often neglected in the design, though it is crucial in practice. In this paper, we present a new 2 3-periodic CFA which provides, by construction, the optimal tradeoff between robustness to aliasing, chrominance noise and luminance noise. Moreover, a simple and efficient linear demosaicking algorithm is described, which fully exploits the spectral properties of the CFA. Practical experiments confirm the superiority of our design, both in noiseless and noisy scenarios.

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