Search results for "Computer vision"

showing 10 items of 2353 documents

Dynamic 3D Scene Reconstruction and Enhancement

2017

International audience; In this paper, we present a 3D reconstruction and enhancement approach for high quality dynamic city scene reconstructions. We first detect and segment the moving objects using 3D Motion Segmenta-tion approach by exploiting the feature trajectories' behaviours. Getting the segmentations of both the dynamic scene parts and the static scene parts, we propose an efficient point cloud registration approach which takes the advantages of 3-point RANSAC and Iterative Closest Points algorithms to produce precise point cloud alignment. Furthermore, we proposed a point cloud smoothing and texture mapping framework to enhance the results of reconstructions for both the static a…

Computer sciencePoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingRANSACPoint Cloud Registration0202 electrical engineering electronic engineering information engineeringSegmentationComputer vision3D Scene Enhancement[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICSMotion Segmentationbusiness.industry3D reconstruction020207 software engineeringFeature (computer vision)Computer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligencebusiness3D Reconstruction[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingTexture mappingSmoothing
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A naive relevance feedback model for content-based image retrieval using multiple similarity measures

2010

This paper presents a novel probabilistic framework to process multiple sample queries in content based image retrieval (CBIR). This framework is independent from the underlying distance or (dis)similarity measures which support the retrieval system, and only assumes mutual independence among their outcomes. The proposed framework gives rise to a relevance feedback mechanism in which positive and negative data are combined in order to optimally retrieve images according to the available information. A particular setting in which users interactively supply feedback and iteratively retrieve images is set both to model the system and to perform some objective performance measures. Several repo…

Computer scienceRelevance feedbackContent-based image retrievalcomputer.software_genreSimilitudeSet (abstract data type)Similarity (network science)Artificial IntelligenceSignal ProcessingComputer Vision and Pattern RecognitionData miningImage retrievalcomputerSoftwareIndependence (probability theory)Pattern Recognition
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Steerable wavelet transform for atlas based retinal lesion segmentation

2013

International audience; Computer aided diagnosis and follow up can help in prevention and treatment of diabetes and its related complications. Screening of diabetes related disease in the eyes is done by a special low cost fundus camera. A follow up of the patients visiting at di fferent time intervals for screening brings us to the problem of image analysis for change detection and its cost per patient. It is very likely that human annotations for the lesions may be erroneous and often time consuming. Since the ethnic background plays a signi cant role in retinal pigment epithelium, visibility of the choroidal vasculature and overall retinal luminance in patients and retinal images, an eth…

Computer scienceRetinal lesionImage processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]LuminanceFundus camera030218 nuclear medicine & medical imaging03 medical and health scienceschemistry.chemical_compound0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicineSegmentationComputer visionRetinaRetinal pigment epitheliumDiabetic Retinopathybusiness.industryAtlas (topology)Atals segmentationWavelet transform[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]RetinalDiabetic retinopathymedicine.diseaseSteerable filtersmedicine.anatomical_structurechemistryComputer-aided diagnosis030221 ophthalmology & optometryRetinal ImageArtificial intelligencebusinessChange detection
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A multi-process system for HEp-2 cells classification based on SVM

2016

An automatic system for pre-segmented IIF images analysis was developed.A non-standard pipeline for supervised image classification was adopted.The system uses a two-level pyramid to retain some spatial information.From each cell image 216 features are extracted.15 SVM classifiers one-against-one have been implemented. This study addresses the classification problem of the HEp-2 cells using indirect immunofluorescence (IIF) image analysis, which can indicate the presence of autoimmune diseases by finding antibodies in the patient serum. Recently, studies have shown that it is possible to identify the cell patterns using IIF image analysis and machine learning techniques. In this paper we de…

Computer scienceSVM02 engineering and technologyImmunofluorescencecomputer.software_genre030218 nuclear medicine & medical imagingImage (mathematics)03 medical and health sciences0302 clinical medicineArtificial IntelligencePyramid0202 electrical engineering electronic engineering information engineeringmedicinePyramid (image processing)Spatial analysisAccuracy1707Contextual image classificationmedicine.diagnostic_testFeatures reductionIndirect immunofluorescencePipeline (software)Class (biology)Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)StainingSupport vector machineHep-2 cells classificationSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionData miningcomputerSoftware
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Automated detection of microaneurysms using robust blob descriptors

2013

International audience; Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fun…

Computer scienceSVMComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyFundus (eye)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringmedicineComputer visionRetinaRadon transformbusiness.industrySURFHessian[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Diabetic retinopathymedicine.diseaseMicroaneurysmSupport vector machinemedicine.anatomical_structureComputer-aided diagnosis020201 artificial intelligence & image processingArtificial intelligencebusinessSVDRetinopathy
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Optical system for automatic color monitoring in heterogeneous media during vinification processes

2019

Abstract Wine is one of the most important food products worldwide. However, the application of technologies to the winemaking process can improve. An RGBC optical sensor, used to measure color intensity and shade, was developed and tested in real environments. It is able to measure samples without filtering by offering the color intensity and shade of a filtered sample. Color intensity can be measured within the range of 1.5 and 9.5 color points with an approximate 3% error. The model for shade can be applied to red wines with an approximate 1% error. It can operate directly in cellars under real operating conditions. It avoids collecting samples, and filtering and measuring in a spectroph…

Computer scienceSample (material)02 engineering and technology010402 general chemistry01 natural sciencesMaterials ChemistryComputer visionElectrical and Electronic EngineeringInstrumentationWinemakingWineMeasure (data warehouse)business.industryMetals and AlloysProcess (computing)Color intensity021001 nanoscience & nanotechnologyCondensed Matter Physics0104 chemical sciencesSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsAnalyticsFood productsArtificial intelligence0210 nano-technologybusinessSensors and Actuators B: Chemical
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Incomplete 3D motion trajectory segmentation and 2D-to-3D label transfer for dynamic scene analysis

2017

International audience; The knowledge of the static scene parts and the moving objects in a dynamic scene plays a vital role for scene modelling, understanding, and landmark-based robot navigation. The key information for these tasks lies on semantic labels of the scene parts and the motion trajectories of the dynamic objects. In this work, we propose a method that segments the 3D feature trajectories based on their motion behaviours, and assigns them semantic labels using 2D-to-3D label transfer. These feature trajectories are constructed by using the proposed trajectory recovery algorithm which takes the loss of feature tracking into account. We introduce a complete framework for static-m…

Computer scienceScene UnderstandingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Motion (physics)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0502 economics and business0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionSegmentationMotion Segmentation050210 logistics & transportationbusiness.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]05 social sciences3D reconstruction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]2D to 3D conversionFeature (computer vision)TrajectoryKey (cryptography)Robot020201 artificial intelligence & image processingArtificial intelligence3D Reconstructionbusiness2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Extracting cloud motion from satellite image sequences

2004

This paper present a new technique for the estimation of cloud motion, using a sequence of infrared satellite images. It can be considered a challenging task due to the complexity of phenomena implied, as non-linear events and a non-rigid motion. In this circumstances most motion models are not suitable and new algorithms have to be developed. We propose a novel method, combining an Automatic Multilevel Thresholding for image segmentation, a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularization.

Computer scienceSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage processingPattern recognitionImage segmentationThresholdingImage textureMotion estimationComputer visionArtificial intelligencebusinessBlock-matching algorithm7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002.
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Feature extraction and correlation for time-to-impact segmentation using log-polar images

2004

In this article we present a technique that allows high-speed movement analysis using the accurate displacement measurement given by the feature extraction and correlation method. Specially, we demonstrate that it is possible to use the time to impact computation for object segmentation. This segmentation allows the detection of objects at different distances.

Computer scienceSegmentation-based object categorizationbusiness.industryFeature (computer vision)Feature extractionScale-space segmentationComputer visionSegmentationPattern recognitionArtificial intelligenceImage segmentationbusinessDisplacement (vector)
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Gabor filtering for feature extraction on complex images: application to defect detection on semiconductors

2006

AbstractThis paper is an extension of previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer inspection is based upon the comparison of the same area on two neighbourhood dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, segmentation is needed to create a mask and apply an optimal threshold in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. This paper shows a method of…

Computer scienceSegmentation-based object categorizationbusiness.industryFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationThresholdingMedia TechnologyWaferComputer visionSegmentationComputer Vision and Pattern RecognitionArtificial intelligencebusinessClassifier (UML)The Imaging Science Journal
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