Search results for "VISION"

showing 10 items of 5066 documents

FastSLAM 2.0: Least-Squares Approach

2006

In this paper, we present a set of robust and efficient algorithms with O(N) cost for the following situations: object detection with a laser ranger; mobile robot pose estimation and a FastSLAM improved implementation. Objected detection is mainly based on a novel multiple line fitting method, related with walls at the environment. This method assumes that walls at the environment constitute a regular constrained angles. A line-based pose estimation method is also proposed, based on Least-Squares (LS). This method performs the matching of detected lines and estimated map lines and it can provide the global pose estimation under assumption of known Data-Association. FastSLAM 1.0 has been imp…

Extended Kalman filterLine fittingComputer sciencebusiness.industryLine (geometry)Mobile robotComputer visionArtificial intelligencebusiness3D pose estimationPoseLeast squaresObject detection2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
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A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics

2006

We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.

Extremal optimizationMathematical optimizationSegmentation-based object categorizationbusiness.industryMulti-agent systemCrossoverComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage segmentationComputingMethodologies_ARTIFICIALINTELLIGENCEComputer Science::Multiagent SystemsArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingSegmentationIterated conditional modesLocal search (optimization)Computer Vision and Pattern RecognitionbusinessAlgorithmSoftwareMathematicsPattern Recognition Letters
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Statistical atlas based exudate segmentation

2013

Diabetic macular edema (DME) is characterized by hard exudates. In this article, we propose a novel statistical atlas based method for segmentation of such exudates. Any test fundus image is first warped on the atlas co-ordinate and then a distance map is obtained with the mean atlas image. This leaves behind the candidate lesions. Post-processing schemes are introduced for final segmentation of the exudate. Experiments with the publicly available HEI-MED data-set shows good performance of the method. A lesion localization fraction of 82.5% at 35% of non-lesion localization fraction on the FROC curve is obtained. The method is also compared to few most recent reference methods.

ExudateComputer scienceFundus imageDiabetic macular edemaHealth Informatics02 engineering and technologyMacular Edema030218 nuclear medicine & medical imaging03 medical and health sciencesAtlases as Topic0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineHumansRadiology Nuclear Medicine and imagingSegmentationComputer visionDiabetic RetinopathyModels StatisticalRadiological and Ultrasound TechnologyAtlas (topology)business.industryExudates and TransudatesComputer Graphics and Computer-Aided DesignUnited StatesHard exudates020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceAnatomic Landmarksmedicine.symptombusinessDistance transformComputerized Medical Imaging and Graphics
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Three-dimentional tracking of human eye

2003

The study of human movements is the object of numerous searches, among them, the study of the face movements and more particularly the eye kinetics estimate represents an important part. A study realized by artificial vision is presented here. It allows to characterize eye movements in normal shooting condition (mobility of the subject, background lighting). Our approach allows to obtain in a simple way the localization of the iris and the characterization of their movement in the three dimensional shape. The absolute 3D movement of eyeballs and their relative movement with regard to the head are obtained, even if this one are moving.

Eye tracking on the ISSMovement (music)business.industryMachine visionIris recognitionEye movementmedicine.anatomical_structureGeographyFace (geometry)medicineEye trackingHuman eyeComputer visionArtificial intelligencebusinessSPIE Proceedings
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Vigor F7 projekta ietekme uz redzes funkcijām

2017

Maģistra darbs ir uzrakstīts angļu valodā uz 38 lapām. Tas satur 12 attēlus, 9 tabulas, 26 atsauces uz literatūras avotiem un 4 pielikumus. Galvenais darba mērķis ir nodemonstrēt F7 ierīces ietekmi uz redzes sistēmu un tās funkcijām. Tika veikti divi eksperimenti: Eksperiments I (30 dalībnieki, 10 – 40 g.v.), lai izvērtētu Vigor F7 ierīces ietekmi uz redzes funkcijām; Eksperiments II (20 dalībnieki, sportisti, 14 – 48 g.v.), lai izvērtētu Vigor F7 ierīces ietekmi uz dinamisko iemaņu efektivitāti. Abos eksperimentos novēroja statistiski nozīmīgi atšķirīgus rezultātus gan redzes funkcijām, gan dinamiskajām iemaņām, ja izmantoja F7 ierīci.

F7 devicevisual performancenobles metalsbalanceFizikasports vision
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RootsGLOH2: embedding RootSIFT 'square rooting' in sGLOH2

2020

This study introduces an extension of the shifting gradient local orientation histogram doubled (sGLOH2) local image descriptor inspired by RootSIFT ‘square rooting’ as a way to indirectly alter the matching distance used to compare the descriptor vectors. The extended descriptor, named RootsGLOH2, achieved the best results in terms of matching accuracy and robustness among the latest state-of-the-art non-deep descriptors in recent evaluation contests dealing with both planar and non-planar scenes. RootsGLOH2 also achieves a matching accuracy very close to that obtained by the best deep descriptors to date. Beside confirming that ‘square rooting’ has beneficial effects on sGLOH2 as it happe…

FEATURE EXTRACTIONLOCAL FEATUREComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformFEATURE MATCHING02 engineering and technologyRobustness (computer science)Euclidean geometryComputer Science::Multimedia0202 electrical engineering electronic engineering information engineeringBeneficial effectsSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryImage matching020206 networking & telecommunicationsPattern recognitionCOMPUTER VISIONImage Matching Local Image Descriptors RootSIFT sGLOH2Computer Science::Computer Vision and Pattern RecognitionEmbedding020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareSquare rootingIMAGE MATCHING
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Remote sensing of sun-induced chlorophyll fluorescence at different scales

2014

In this contribution we present activities and selected results obtained in recent studies and campaigns conducted in the context of the FLuorescence EXplorer (FLEX) mission. FLEX is a candidate mission for the ESA 8th Earth Explorer and large efforts are currently dedicated to the development of an implementation scheme for an accurate mapping of fluorescence from the selected spaceborne sensor and mission configuration. Field and airborne data collected in different experimental campaigns, together with simulated data, have been used to demonstrate the feasibility of fluorescence retrievals and the potential of exploiting high spatial resolution fluorescence maps for a better understandin…

FLORISfield measurementComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHyperspectral imagingContext (language use)Atmospheric modelFLEX missionGeneralLiterature_MISCELLANEOUSRemote sensing (archaeology)Simulated datafield measurementsHyPlantSun-induced chlorophyll fluorescenceHigh spatial resolutionEnvironmental scienceFLEXChlorophyll fluorescenceRemote sensing2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
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On the Greedy Algorithm for the Shortest Common Superstring Problem with Reversals

2015

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem Shortest Common Superstring with Reversals (SCS-R). This problem has been introduced by Jiang et al., who designed a greedy-like algorithm with length approximation ratio $4$. In this paper, we show that a natural adaptation of the classical greedy algorithm for SCS has (optimal) compression ratio $\frac12$, i.e., the sum of the overlaps in the output string is at least half the sum of the overlaps in an optimal solution. We also provide a linear-time implement…

FOS: Computer and information sciences0102 computer and information sciences02 engineering and technologyInformation System01 natural sciencesString (physics)Theoretical Computer ScienceCombinatoricsHigh Energy Physics::TheoryAnalysis of algorithmGreedy algorithmComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)Greedy algorithmFinite setAnalysis of algorithmsMathematicsSuperstring theoryShortest Common SuperstringComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsReversalShortest Path Faster Algorithm010201 computation theory & mathematicsCompression ratioSignal Processing020201 artificial intelligence & image processingK shortest path routingInformation Systems
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Spectral band selection for vegetation properties retrieval using Gaussian processes regression

2020

Abstract With current and upcoming imaging spectrometers, automated band analysis techniques are needed to enable efficient identification of most informative bands to facilitate optimized processing of spectral data into estimates of biophysical variables. This paper introduces an automated spectral band analysis tool (BAT) based on Gaussian processes regression (GPR) for the spectral analysis of vegetation properties. The GPR-BAT procedure sequentially backwards removes the least contributing band in the regression model for a given variable until only one band is kept. GPR-BAT is implemented within the framework of the free ARTMO's MLRA (machine learning regression algorithms) toolbox, w…

FOS: Computer and information sciences010504 meteorology & atmospheric sciencesComputer Vision and Pattern Recognition (cs.CV)0211 other engineering and technologiesComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyManagement Monitoring Policy and Law01 natural sciencesStatistics - Applicationssymbols.namesakeFOS: Electrical engineering electronic engineering information engineeringApplications (stat.AP)Computers in Earth SciencesGaussian processHyMap021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingGlobal and Planetary ChangeImage and Video Processing (eess.IV)Hyperspectral imagingRegression analysisVegetationSpectral bands15. Life on landElectrical Engineering and Systems Science - Image and Video ProcessingRegressionGeographyGround-penetrating radarsymbolsInternational Journal of Applied Earth Observation and Geoinformation
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Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook

2022

The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These new methods provide analysis of data from sensors, cameras, and acoustic recorders, even in real time, in ways that are reproducible and rapid. Off-the-shelf algorithms can find, count, and classify species from digital images or video and detect cryptic patterns in noisy data. Using these opportunities requires collaboration across ecological and data science disciplines, which can be challenging to initiate. To facilitate these collaborations and promote the use of deep learning towards ecosystem-based management…

FOS: Computer and information sciences0106 biological sciencesArtificial intelligenceComputer Science - Machine LearningEcologyComputer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)010604 marine biology & hydrobiologyComputer Science - Computer Vision and Pattern RecognitionMarine monitoringMarine bioacousticsAquatic ScienceEcosystem-based managementOceanography010603 evolutionary biology01 natural sciencesMachine Learning (cs.LG)VDP::Teknologi: 500Artificial Intelligence (cs.AI)13. Climate actionMachine learning14. Life underwaterEcology Evolution Behavior and Systematics
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