Search results for "computer vision"

showing 10 items of 2353 documents

3D Map Computation from Historical Stereo Photographs of Florence

2018

The analysis of early photographic sources is fundamental for documenting and understanding the evolution of a city so rich in history and art as Florence. Indeed, by the 1860s several photographers used to work in town, and their images (often obtained through stereoscopic set-ups) can help us to reconstruct Florence in 3D as it was by the time of the Italian unification. The first and most delicate part of such reconstruction process is the computation of disparity maps from the historical stereo pairs. This is a very challenging task for fully-automatic computer vision algorithms, since XIX century photographs are affected by several problems—ranging from superficial damages to asynchron…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - InformaticaUnificationComputer scienceComputationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)020207 software engineeringStereoscopy02 engineering and technologyPhotography Computer vision algorithms Disparity map Florence Reconstruction process Semiautomatic methods Stereo pair Stereo-photographs User input Stereo image processingUser inputlaw.inventionAsynchronous communicationlawComputer graphics (images)0202 electrical engineering electronic engineering information engineering3D Stereo Historical Photographs Cultural Heritage Computer VisionComputer vision algorithms020201 artificial intelligence & image processingComputingMethodologies_COMPUTERGRAPHICSIOP Conference Series: Materials Science and Engineering
researchProduct

Is There Anything New to Say About SIFT Matching?

2020

SIFT is a classical hand-crafted, histogram-based descriptor that has deeply influenced research on image matching for more than a decade. In this paper, a critical review of the aspects that affect SIFT matching performance is carried out, and novel descriptor design strategies are introduced and individually evaluated. These encompass quantization, binarization and hierarchical cascade filtering as means to reduce data storage and increase matching efficiency, with no significant loss of accuracy. An original contextual matching strategy based on a symmetrical variant of the usual nearest-neighbor ratio is discussed as well, that can increase the discriminative power of any descriptor. Th…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryComputer scienceImage matchingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformPattern recognition02 engineering and technologySIFT sGLOH2 Quantization Binary descriptors Symmetric matching Hierarchical cascade filtering Deep descriptors Keypoint patch orientation Approximated overlap errorDiscriminative modelArtificial IntelligenceHistogramComputer data storage0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceSIFTsGLOH2quantizationbinary descriptorssymmetric matchinghierarchical cascade filteringdeep descriptorskeypoint patch orientationapproximated overlap errorbusinessQuantization (image processing)SoftwareInternational Journal of Computer Vision
researchProduct

Editorial for special issue “fine art pattern extraction and recognition”

2021

: Cultural heritage, especially the fine arts, plays an invaluable role in the cultural, historical, and economic growth of our societies [...].

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticacultural heritagecomputer visionimage processing
researchProduct

Guest editorial: Local image descriptors in computer vision

2020

...This Special Issue includes seven original research papers that cover diverse and significant aspects of local image descriptor research. In particular, the order in which papers appear reflects the main phase they address, in an ideal computational pipeline starting with the localisation of salient points in an image and ending with the incorporation of spatial and temporal features in descriptor construction....

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticalocal descriptorscomputer vision
researchProduct

Retinal image synthesis through the least action principle

2020

Eye fundus image analysis is a fundamental approach in medical diagnosis and follow-up ophthalmic diagnostics. Manual annotation by experts needs hard work, thus only a small set of annotated vessel structures is available. Examples such as DRIVE and STARE include small sets for training images of fundus image benchmarks. Moreover, there is no vessel structure annotation for a number of fundus image datasets. Synthetic images have been generated by using appropriate parameters for the modeling of vascular networks or by methods developing deep learning techniques and supported by performance hardware. Our methodology aims to produce high-resolution synthetic fundus images alternative to the…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticapredictive evaluation diseasesComputer sciencebusiness.industryDeep learningComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFundus (eye)Real imageSmall setPrinciple of least actionImage (mathematics)fundus image analysisAnnotationComputer visionArtificial intelligenceMedical diagnosisbusinessstatistical featuressynthetic retinal imagedata augmentation2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)
researchProduct

A Low Cost Solution for NOAA Remote Sensing

2018

United States National Oceanic and Atmospheric Administration (NOAA) weather satellites adopt Advanced Very High Resolution Radiometer (AVHRR) sensors to acquire remote sensing data and broadcast Automatic Picture Transmission (APT) images. The orientation of the scan lines is perpendicular to the orbit of the satellite. In this paper we propose a new low cost solution for NOAA remote sensing. More in detail, our method focuses on the possibility of directly sampling the modulated signal and processing it entirely in software enabled by recent breakthroughs on Software Defined Radios (SDR) and CPU computational speed, while keeping the costs extremely low. We aim to achieve good results wit…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSignal processingComputer Networks and CommunicationsComputer science0211 other engineering and technologiesComputer Science Applications1707 Computer Vision and Pattern RecognitionInformation System02 engineering and technologyRemote SensingRemote sensing (archaeology)Signal ProcessingInformation systemCommunications satelliteSatellite CommunicationElectrical and Electronic Engineering021101 geological & geomatics engineeringRemote sensingProceedings of the 7th International Conference on Sensor Networks
researchProduct

Medical image registration: Interpolations, similarities and optimizations strategies

2010

This paper presents a study conducted for evaluating different interpolation schemes, similarity metrics and optimization algorithms for the purpose of volumetric medical image registration. Each technique has been implemented to be plugged in a modular system. Rotation, translation and scale error has been measured to obtain a performance evaluation for all of the combinations of the considered techniques. Several experimental tests were conducted for validation both on synthetic and real datasets providing an exhaustive overview of the various strategies used.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSimilarity (geometry)business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationTranslation (geometry)computer.software_genreHigh-definition videoMedical imagingMeasurement uncertaintyComputer visionMedical Image RegistrationArtificial intelligenceData miningbusinesscomputerRotation (mathematics)Interpolation2010 IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS)
researchProduct

Effective and Efficient Interpolation for Mutual Information based Multimodality Elastic Image Registration

2009

Mutual information (MI) is a popular similarity metric for multimodality image registration purpose. However, it is negatively influenced by artifacts due to interpolation effects. As a result, registration algorithms performance could be affected. In this paper a novel interpolation scheme is presented. It is both effective and efficient. Effective because it limits the presence of local maxima in the mutual information curve, efficient because it is simple to compute being based on simple and optimized distance measures. The method is validated and compared against other techniques both from performance and time complexity persepectives. Differently from other reference works, which perfo…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSimilarity (geometry)business.industryImage registrationMutual informationinterpolation mutual information elastic registration non-linear optimizationDistance measuresHistogramMetric (mathematics)Computer visionArtificial intelligencebusinessAlgorithmRigid transformationMathematicsInterpolation
researchProduct

Image Segmentation through a Hierarchy of Minimum Spanning Trees

2012

Many approaches have been adopted to solve the problem of image segmentation. Among them a noticeable part is based on graph theory casting the pixels as nodes in a graph. This paper proposes an algorithm to select clusters in the images (corresponding to relevant segments in the image) corresponding to the areas induced in the images through the search of the Minimum Spanning Tree (MST). In particular is is based on a clustering algorithm that extracts clusters computing a hierarchy of Minimum Spanning Trees. The main drawback of this previous algorithm is that the dimension of the cluster is not predictable and a relevant portion of found clusters can be composed by micro-clusters that ar…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSpanning treebusiness.industrySingle-linkage clusteringComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionImage segmentationMinimum spanning treeImage SegmentationMinimum Spanning TreesClusteringDistributed minimum spanning treeMinimum spanning tree-based segmentationKruskal's algorithmArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionReverse-delete algorithmArtificial intelligencebusinessMathematics
researchProduct

Piecewise planar underwater mosaicing

2015

A commonly ignored problem in planar mosaics, yet often present in practice, is the selection of a reference homography reprojection frame where to attach the successive image frames of the mosaic. A bad choice for the reference frame can lead to severe distortions in the mosaic and can degenerate in incorrect configurations after some sequential frame concatenations. This problem is accentuated in uncontrolled underwater acquisition setups as those provided by AUVs or ROVs due to both the noisy trajectory of the acquisition vehicle — with roll and pitch shakes — and to the non-flat nature of the seabed which tends to break the planarity assumption implicit in the mosaic construction. These…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSustainability and the EnvironmentSettore INF/01 - Informaticabusiness.industryColor correctionFrame (networking)Remotely operated underwater vehicleOceanographyRenewable Energy Sustainability and the Environment; OceanographyColor correction Experimental evaluation Image frames Mosaic construction Noisy trajectory Re-projection Reference frame Video sequencesColors of noisePiecewiseComputer visionArtificial intelligenceNoise (video)Renewable EnergybusinessReference frameHomography (computer vision)Mathematics
researchProduct