Search results for "InGaN"

showing 10 items of 1214 documents

noRANSAC for fundamental matrix estimation

2011

The estimation of the fundamental matrix from a set of corresponding points is a relevant topic in epipolar stereo geometry [10]. Due to the high amount of outliers between the matches, RANSAC-based approaches [7, 13, 29] have been used to obtain the fundamental matrix. In this paper two new contributes are presented: a new normalized epipolar error measure which takes into account the shape of the features used as matches [17] and a new strategy to compare fundamental matrices. The proposed error measure gives good results and it does not depend on the image scale. Moreover, the new evaluation strategy describes a valid tool to compare diffe rent RANSAC-based methods because it does not re…

Evaluation strategyGround truthSettore INF/01 - Informaticabusiness.industryimage features epipolar geometry ransac fundamental matrix estimationEight-point algorithmEpipolar geometryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage scaleRANSACOutlierComputer visionArtificial intelligencebusinessFundamental matrix (computer vision)AlgorithmMathematicsProcedings of the British Machine Vision Conference 2011
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Infrared image processing and its application to forest fire surveillance

2007

This paper describes an scheme for automatic forest surveillance. A complete system for forest fire detection is firstly presented although we focus on infrared image processing. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the system related with probability of false alarm (PFA). Probability of detection (PD) dependence on sign…

ExploitComputer scienceFire detectionbusiness.industryReal-time computingDetectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingStatistical powerInfrared image processingComputer visionArtificial intelligenceFalse alarmFocus (optics)business2007 IEEE Conference on Advanced Video and Signal Based Surveillance
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Eliciting Information on the Vulnerability Black Market from Interviews

2010

Threats to computing prompted by software vulnerabilities are abundant and costly for those affected. Adding to this problem is the emerging vulnerability black markets (VBMs), since they become places to trade malware and exploits. VBMs are discussed based on information derived from interviews with security researchers. The effort is enriched by further examination of documents surrounding the disclosure of four selected vulnerabilities cases. The result suggests that the VBMs is bifurcated into two distinct parts; the skilled-hacker and the script-kiddie VBMs with a possible link between them, where the latter become places to sell malware or exploit kits after the zero day vulnerability…

ExploitComputer sciencebusiness.industryInternet privacycomputer.software_genreComputer securitySoftware qualityElectronic mailComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMSMalwareBlack marketbusinesscomputerZero-day attackVulnerability (computing)2010 Fourth International Conference on Emerging Security Information, Systems and Technologies
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Automatic image representation for content-based access to personal photo album

2007

The proposed work exploits methods and techniques for automatic characterization of images for content-based access to personal photo libraries. Several techniques, even if not reliable enough to address the general problem of content-based image retrieval, have been proven quite robust in a limited domain such as the one of personal photo album. In particular, starting from the observation that most personal photos depict a usually small number of people in a relatively small number of different contexts (e.g. Beach, Public Garden, Indoor, Nature, Snow, City, etc...) we propose the use of automatic techniques borrowed from the fields of computer vision and pattern recognition to index imag…

Exploitbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContext (language use)Term (time)Domain (software engineering)Index (publishing)Pattern recognition (psychology)Computer visionArtificial intelligenceFace detectionbusinessImage retrieval
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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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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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Polarimetric image augmentation

2021

Robotics applications in urban environments are subject to obstacles that exhibit specular reflections hampering autonomous navigation. On the other hand, these reflections are highly polarized and this extra information can successfully be used to segment the specular areas. In nature, polarized light is obtained by reflection or scattering. Deep Convolutional Neural Networks (DCNNs) have shown excellent segmentation results, but require a significant amount of data to achieve best performances. The lack of data is usually overcomed by using augmentation methods. However, unlike RGB images, polarization images are not only scalar (intensity) images and standard augmentation techniques cann…

FOS: Computer and information sciences0209 industrial biotechnologyAugmentation procedurebusiness.industryComputer Vision and Pattern Recognition (cs.CV)Deep learningComputer Science - Computer Vision and Pattern RecognitionPolarimetryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technologyImage segmentationConvolutional neural networkData modeling[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionSegmentationArtificial intelligenceSpecular reflectionbusiness
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P2D: a self-supervised method for depth estimation from polarimetry

2021

Monocular depth estimation is a recurring subject in the field of computer vision. Its ability to describe scenes via a depth map while reducing the constraints related to the formulation of perspective geometry tends to favor its use. However, despite the constant improvement of algorithms, most methods exploit only colorimetric information. Consequently, robustness to events to which the modality is not sensitive to, like specularity or transparency, is neglected. In response to this phenomenon, we propose using polarimetry as an input for a self-supervised monodepth network. Therefore, we propose exploiting polarization cues to encourage accurate reconstruction of scenes. Furthermore, we…

FOS: Computer and information sciences0209 industrial biotechnologyMonocularComputer sciencebusiness.industryComputer Vision and Pattern Recognition (cs.CV)PolarimetryComputer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology010501 environmental sciences01 natural sciencesRegularization (mathematics)Term (time)020901 industrial engineering & automation[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]SpecularityRobustness (computer science)Depth mapComputer visionArtificial intelligenceTransparency (data compression)business0105 earth and related environmental sciences
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Pattern Recognition Scheme for Large-Scale Cloud Detection over Landmarks

2020

Landmark recognition and matching is a critical step in many Image Navigation and Registration (INR) models for geostationary satellite services, as well as to maintain the geometric quality assessment (GQA) in the instrument data processing chain of Earth observation satellites. Matching the landmark accurately is of paramount relevance, and the process can be strongly impacted by the cloud contamination of a given landmark. This paper introduces a complete pattern recognition methodology able to detect the presence of clouds over landmarks using Meteosat Second Generation (MSG) data. The methodology is based on the ensemble combination of dedicated support vector machines (SVMs) dependent…

FOS: Computer and information sciencesAtmospheric ScienceMatching (statistics)Computer Science - Machine LearningSource code010504 meteorology & atmospheric sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)media_common.quotation_subjectMultispectral image0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputer Science - Computer Vision and Pattern RecognitionCloud computing02 engineering and technology01 natural sciencesMachine Learning (cs.LG)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesmedia_commonLandmarkbusiness.industryPattern recognitionSupport vector machinePattern recognition (psychology)Geostationary orbitArtificial intelligencebusiness
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