Search results for "Depth estimation"

showing 5 items of 5 documents

Area-Based Depth Estimation for Monochromatic Feature-Sparse Orthographic Capture

2018

With the rapid development of light field technology, depth estimation has been highlighted as one of the critical problems in the field, and a number of approaches have been proposed to extract the depth of the scene. However, depth estimation by stereo matching becomes difficult and unreliable when the captured images lack both color and feature information. In this paper, we propose a scheme that extracts robust depth from monochromatic, feature-sparse scenes recorded in orthographic sub-aperture images. Unlike approaches which rely on the rich color and texture information across the sub-aperture views, our approach is based on depth from focus techniques. First, we superimpose shifted …

Computer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContext (language use)02 engineering and technologyimatges processamentDepth map0202 electrical engineering electronic engineering information engineeringorthographic viewsComputer visionComputingMethodologies_COMPUTERGRAPHICSSignal processingComputer Sciencesbusiness.industryOrthographic projectionmicroscòpia020207 software engineeringintegral imagingDatavetenskap (datalogi)Feature (computer vision)depth from focusComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingMonochromatic colorArtificial intelligenceDepth estimationbusinessFocus (optics)Light field2018 26th European Signal Processing Conference (EUSIPCO)
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Compréhension de scènes urbaines basée sur la polarisation

2021

Humans possess an innate ability to interpret scenes under any condition. Computer Vision tends to mimic these capabilities by implementing intelligent algorithms to address complex understanding problems. In this regard, we are interested in understanding outdoor urban scenes in various weather conditions. This thesis specifically addresses the problems arising from the presence of specularity in the scenes. To this end, we aim to take advantage of polarization indices to define such surfaces in addition to traditional objects. In terms of understanding, we aim to introduce polarization to the fields of computer vision and deep learning.This thesis focuses on the following underlying chall…

Deep LearningSegmentation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer VisionVision par ordinateurPolarimetryScene understandingDepth estimationEstimation de profondeurPolarimétrieCompréhension de scène
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A Dataset of Annotated Omnidirectional Videos for Distancing Applications

2021

Omnidirectional (or 360°) cameras are acquisition devices that, in the next few years, could have a big impact on video surveillance applications, research, and industry, as they can record a spherical view of a whole environment from every perspective. This paper presents two new contributions to the research community: the CVIP360 dataset, an annotated dataset of 360° videos for distancing applications, and a new method to estimate the distances of objects in a scene from a single 360° image. The CVIP360 dataset includes 16 videos acquired outdoors and indoors, annotated by adding information about the pedestrians in the scene (bounding boxes) and the distances to the camera of some point…

distancingComputer scienceDistancing360°Computer applications to medicine. Medical informaticsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONR858-859.7Pedestrianvideo datasetArticleImage (mathematics)Bounding overwatchResearch communityomnidirectional camerasdepth estimationPhotographyRadiology Nuclear Medicine and imagingComputer visionvideo surveillanceElectrical and Electronic EngineeringOmnidirectional antennaTR1-1050360Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionispherical imagesbusiness.industryPerspective (graphical)Process (computing)QA75.5-76.95trackingComputer Graphics and Computer-Aided Designequirectangular projectionElectronic computers. Computer sciencepedestrianComputer Vision and Pattern RecognitionArtificial intelligencebusinessJournal of Imaging
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Compréhension de scènes urbaines basées sur la polarisation

2021

Humans possess an innate ability to interpret scenes under any condition. Computer Vision tends to mimic these capabilities by implementing intelligent algorithms to address complex understanding problems. In this regard, we are interested in understanding outdoor urban scenes in various weather conditions. This thesis specifically addresses the problems arising from the presence of specularity in the scenes. To this end, we aim to take advantage of polarization indices to define such surfaces in addition to traditional objects. In terms of understanding, we aim to introduce polarization to the fields of computer vision and deep learning.This thesis focuses on the following underlying challeng…

Deep LearningSegmentation[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]PolarimetryScene Understanding[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Estimation de profondeurDepth EstimationPolarimétrieCompréhension de scènes
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Robust Depth Estimation for Light Field Microscopy

2019

Light field technologies have seen a rise in recent years and microscopy is a field where such technology has had a deep impact. The possibility to provide spatial and angular information at the same time and in a single shot brings several advantages and allows for new applications. A common goal in these applications is the calculation of a depth map to reconstruct the three-dimensional geometry of the scene. Many approaches are applicable, but most of them cannot achieve high accuracy because of the nature of such images: biological samples are usually poor in features and do not exhibit sharp colors like natural scene. Due to such conditions, standard approaches result in noisy depth ma…

MicroscopemicroscopeComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologylcsh:Chemical technologyBiochemistryArticleAnalytical Chemistrylaw.inventionsymbols.namesakelawDepth mapMicroscopy0202 electrical engineering electronic engineering information engineeringdepth estimationlight fieldlcsh:TP1-1185Computer visionElectrical and Electronic Engineeringstereo matchingInstrumentationLight field microscopydefocusbusiness.industryÒptica021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsField (geography)MicroscòpiaFourier transformsymbols020201 artificial intelligence & image processingArtificial intelligenceNoise (video)0210 nano-technologybusinessLight fieldSensors
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