Search results for " Soft"

showing 10 items of 1710 documents

Qualifying semantic graphs using model checking

2011

International audience; Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of research concerns t…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web0102 computer and information sciences02 engineering and technologycomputer.software_genre01 natural sciencesSocial Semantic Webtemporal logicSemantic similaritySemantic computing0202 electrical engineering electronic engineering information engineeringSemantic analyticsSemantic integrationSemantic Web StackInformation retrievalbusiness.industry[INFO.INFO-WB]Computer Science [cs]/WebSemantic search020207 software engineeringSemantic interoperability[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModel-checking010201 computation theory & mathematicsSemantic graphTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS[INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationArtificial intelligencebusinesscomputerNatural language processing2011 International Conference on Innovations in Information Technology
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Region-based segmentation on depth images from a 3D reference surface for tree species recognition.

2013

International audience; The aim of the work presented in this paper is to develop a method for the automatic identification of tree species using Terrestrial Light Detection and Ranging (T-LiDAR) data. The approach that we propose analyses depth images built from 3D point clouds corresponding to a 30 cm segment of the tree trunk in order to extract characteristic shape features used for classifying the different tree species using the Random Forest classifier. We will present the method used to transform the 3D point cloud to a depth image and the region based segmentation method used to segment the depth images before shape features are computed on the segmented images. Our approach has be…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingFeature extractionPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Minimum spanning tree-based segmentation[STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringSegmentationComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[STAT.AP]Statistics [stat]/Applications [stat.AP]Contextual image classificationbusiness.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentation15. Life on landdepth image segmentationRandom forestdepth images from 3D point cloudsIEEE[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingsingle tree species recognitionArtificial intelligenceRange segmentationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingForest inventory
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Integration of 3D and multispectral data for cultural heritage applications: Survey and perspectives

2013

International audience; Cultural heritage is increasingly put through imaging systems such as multispectral cameras and 3D scanners. Though these acquisition systems are often used independently, they collect complementary information (spectral vs. spatial) used for the study, archiving and visualization of cultural heritage. Recording 3D and multispectral data in a single coordinate system enhances the potential insights in data analysis. Wepresent the state of the art of such acquisition systems and their applications for the study of cultural her- itage. Wealso describe existing registration techniques that can be used to obtain 3D models with multispec- tral texture and explore the idea…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingRegistration[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION3d model[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologycomputer.software_genre3D digitizationMultispectral imaging[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. Sustainability0202 electrical engineering electronic engineering information engineering[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMultispectral dataMultimedia020207 software engineeringData fusionSensor fusionData scienceVisualizationCultural heritagePhotogrammetryPhotogrammetrySignal ProcessingCultural heritage020201 artificial intelligence & image processingComputer Vision and Pattern Recognition[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingcomputerImage and Vision Computing
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Smart camera design for realtime High Dynamic Range imaging

2011

International audience; Many camera sensors suffer from limited dynamic range. The result is that there is a lack of clear details in displayed images and videos. This paper describes our approach to generate high dynamic range (HDR) from an image sequence while modifying exposure times for each new frame. For this purpose, we propose an FPGA-based architecture that can produce a real-time high dynamic range video from successive image acquisition. Our hardware platform is build around a standard low dynamic range CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and embedded image pre…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingACM IEEEImagingVideosHardware[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHigh-dynamic-range imaging0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensorImage resolutionHigh dynamic range[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPipelinesCMOS sensorDynamic rangePixelbusiness.industrySensors020208 electrical & electronic engineeringReal time systems020207 software engineeringFrame rate[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Asserting the Precise Position of 3D and Multispectral Acquisition Systems for Multisensor Registration Applied to Cultural Heritage Analysis

2012

International audience; We present a novel method to register multispectral acquisitions on a 3D model. The method is based on the external tracking of the acquisition systems using close-range photogrammetric techniques: multiple calibrated cameras simultaneously observe the successive acquisition systems in use. The views from these cameras are used to precisely determine the position of each acquisition system. All datasets can then be projected in the same coordinate system. The registration is thus independent from the quality and content of the data. This method is well suited to the study of cultural heritage or any other application where we do not wish to place targets on the objec…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceCoordinate systemMultispectral image02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingclose range photogrammetryTracking (particle physics)multispectral acquisitions[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPosition (vector)0202 electrical engineering electronic engineering information engineeringComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing2d-3d registrationbusiness.industry020207 software engineeringcultural heritageObject (computer science)Pipeline (software)optical calibrationCultural heritage3d digitizationPhotogrammetry020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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HDR-ARtiSt: High Dynamic Range Advanced Real-Time Imaging System

2012

International audience; This paper describes the HDR-ARtiSt hardware platform, a FPGA-based architecture that can produce a real- time high dynamic range video from successive image acquisition. The hardware platform is built around a standard low dynamic range (LDR) CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and em- bedded image pre-processing capabilities including multiframe acquisition with various exposure times. Our approach consists of a hardware architecture with different algorithms: double exposure control during image capture, building of an HDR image by combining the…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceHardware platformReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingVideo camera02 engineering and technologyTone mapping[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processinglaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawHistogram0202 electrical engineering electronic engineering information engineeringHigh dynamic rangeFPGA[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingHardware architectureCMOS sensorLiquid-crystal displayreal timePixelbusiness.industryDynamic range020207 software engineeringHigh Dynamic RangeFrame rate[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronicsimage processing[SPI.TRON]Engineering Sciences [physics]/ElectronicsIEEE020201 artificial intelligence & image processingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputer hardware
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Registration of 3D and Multispectral Data for the Study of Cultural Heritage Surfaces

2013

International audience; We present a technique for the multi-sensor registration of featureless datasets based on the photogrammetric tracking of the acquisition systems in use. This method is developed for the in situ study of cultural heritage objects and is tested by digitizing a small canvas successively with a 3D digitization system and a multispectral camera while simultaneously tracking the acquisition systems with four cameras and using a cubic target frame with a side length of 500 mm. The achieved tracking accuracy is better than 0.03 mm spatially and 0.150 mrad angularly. This allows us to seamlessly register the 3D acquisitions and to project the multispectral acquisitions on th…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyclose range photogrammetryTracking (particle physics)computer.software_genrelcsh:Chemical technologyBiochemistryArticle3D digitizationAnalytical Chemistry[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. Sustainability2D-3D registration0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionlcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationDigitization[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMultispectral dataMultimediabusiness.industryFrame (networking)020207 software engineeringcultural heritageAtomic and Molecular Physics and Opticsoptical calibrationCultural heritagePhotogrammetrydigitization020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSensors
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The non-degenerate Dupin cyclides in the space of spheres using Geometric Algebra

2012

International audience; Dupin cyclides are algebraic surfaces of degree 4 discovered by the French mathematician Pierre-Charles Dupin early in the 19th century and \textcolor{black}{were} introduced in CAD by R. Martin in 1982. A Dupin cyclide can be defined, in two different ways, as the envelope of a one-parameter family of oriented spheres. So, it is very interesting to model the Dupin cyclides in the space of spheres, space wherein each family of spheres can be seen as a conic curve. In this paper, we model the non-degenerate Dupin cyclides and the space of spheres using Conformal Geometric Algebra. This new approach permits us to benefit from the advantages of the use of Geometric Alge…

[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]Dupin cyclideDupin cyclide[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]010103 numerical & computational mathematics02 engineering and technologySpace (mathematics)[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]01 natural sciencesGeometric algebra[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]space of spheresAlgebraic surface0202 electrical engineering electronic engineering information engineering0101 mathematicsComputingMilieux_MISCELLANEOUSMathematicsconformal geometric algebraApplied MathematicsDegenerate energy levelsConformal geometric algebra020207 software engineering[ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR][INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]AlgebraConic section[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]SPHERES
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A predictive approach for a real-time remote visualization of large meshes

2012

Déjà sur HAL; Remote access to large meshes is the subject of studies since several years. We propose in this paper a contribution to the problem of remote mesh viewing. We work on triangular meshes. After a study of existing methods of remote viewing, we propose a visualization approach based on a client-server architecture, in which almost all operations are performed on the server. Our approach includes three main steps: a first step of partitioning the original mesh, generating several fragments of the original mesh that can be supported by the supposed smaller Transfer Control Protocol (TCP) window size of the network, a second step called pre-simplification of the mesh partitioned, ge…

[ MATH.MATH-GT ] Mathematics [math]/Geometric Topology [math.GT]geometrytopologyComputer scienceSynthèse d'image et réalité virtuelle [Informatique]Distributed computingSewingContext (language use)02 engineering and technologySolid modeling[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]SimplificationvisualisationData visualizationtopology.[MATH.MATH-GT]Mathematics [math]/Geometric Topology [math.GT]Serverpartitioning0202 electrical engineering electronic engineering information engineeringPolygon meshVisualization[MATH.MATH-GT] Mathematics [math]/Geometric Topology [math.GT]Meshbusiness.industryProcess (computing)simplification020207 software engineering[ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR][INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]VisualizationIEEEmesh[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]Mesh generation[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]020201 artificial intelligence & image processingbusinesssewingPartitioning
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Semantic User Profiling for Digital Advertising

2015

International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Data AnalysisBig DataACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.5: Online Information Services[ INFO ] Computer Science [cs]OntologyACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and IndexingACM : H.: Information SystemsUser ProfilingACM: H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONSReasoningACM : H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONS[INFO] Computer Science [cs][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software/H.3.4.5: User profiles and alert servicesACM: H.: Information SystemsInferenceACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.5: Online Information Services[INFO]Computer Science [cs]Logical Rules[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and IndexingSWRLACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software/H.3.4.5: User profiles and alert servicesSemantic Web
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