Search results for " pattern"

showing 10 items of 2245 documents

An evaluation of recent local image descriptors for real-world applications of image matching

2019

This paper discusses and compares the best and most recent local descriptors, evaluating them on increasingly complex image matching tasks, encompassing planar and non-planar scenarios under severe viewpoint changes. This evaluation, aimed at assessing descriptor suitability for real-world applications, leverages the concept of approximated overlap error as a means to naturally extend to non-planar scenes the standard metric used for planar scenes. According to the evaluation results, most descriptors exhibit a gradual performance degradation in the transition from planar to non-planar scenes. The best descriptors are those capable of capturing well not only the local image context, but als…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - InformaticaImage matchingComputer sciencebusiness.industryVisual descriptorsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognition02 engineering and technology03 medical and health sciences0302 clinical medicineLocal Image Descriptors; Image MatchingRobustness (computer science)Computer Science::Computer Vision and Pattern RecognitionComputer Science::Multimedia030221 ophthalmology & optometry0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessImage matching Data-driven approach Descriptors Evaluation results Local descriptors Local image descriptors Performance degradation Real-worldScene structure Computer vision
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

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

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

Entropy-based Localization of Textured Regions

2011

Appearance description is a relevant field in computer vision that enables object recognition in domains as re-identification, retrieval and classification. Important cues to describe appearance are colors and textures. However, in real cases, texture detection is challenging due to occlusions and to deformations of the clothing while person's pose changes. Moreover, in some cases, the processed images have a low resolution and methods at the state of the art for texture analysis are not appropriate. In this paper, we deal with the problem of localizing real textures for clothing description purposes, such as stripes and/or complex patterns. Our method uses the entropy of primitive distribu…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniTexture atlasComputer sciencebusiness.industryLocal binary patternsLow resolutionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCognitive neuroscience of visual object recognitionLatent Dirichlet allocationsymbols.namesakesymbolsEntropy (information theory)SegmentationComputer visionArtificial intelligencebusinessimage analysis textureComputingMethodologies_COMPUTERGRAPHICS
researchProduct

Separation of Concerns and Role Implementation in the PASSI Design Process

2007

The use of design patterns proved successful in lowering the development time and number of errors when producing software with the object-oriented paradigm. In previous works we engaged the production of a tool for the reuse of patterns for multi-agent systems. Now we are fronting a new problem: automatic code generation for agents, designed with a specific methodology, with the support of design patterns and using an aspect oriented approach. In this work we present our preliminary experiences in the identification, description, production and use of aspects for multi agent systems and a tool for code production.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceAspect-oriented programmingMulti-agent systemSeparation of concernsReuseSoftware agentSoftware design patternSystems engineeringDesign processCode generationSoftware engineeringbusinessComputer softwareMulti agent systemsObject oriented programmingProblem solving2007 5th IEEE International Conference on Industrial Informatics
researchProduct

Iterative Multiple Bounding-Box Refinements for Visual Tracking.

2022

Single-object visual tracking aims at locating a target in each video frame by predicting the bounding box of the object. Recent approaches have adopted iterative procedures to gradually refine the bounding box and locate the target in the image. In such approaches, the deep model takes as input the image patch corresponding to the currently estimated target bounding box, and provides as output the probability associated with each of the possible bounding box refinements, generally defined as a discrete set of linear transformations of the bounding box center and size. At each iteration, only one transformation is applied, and supervised training of the model may introduce an inherent ambig…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionideep trackingiterative bounding box refinementRadiology Nuclear Medicine and imagingComputer Vision and Pattern RecognitionElectrical and Electronic Engineeringvisual trackingComputer Graphics and Computer-Aided Designvisual tracking; deep tracking; iterative bounding box refinementJournal of imaging
researchProduct

Towards a Smart Campus Through Participatory Sensing

2018

In recent years, the percentage of the population owning a smartphone has increased significantly. These devices provide users with more and more functions that make them real sensing platforms. Exploiting the capabilities offered by smartphones, users can collect data from the surrounding environment and share them with other entities in the network thanks to existing communication infrastructures, i.e., 3G/4G/5G or WiFi. In this work, we present a system based on participatory sensing paradigm using smartphones to collect and share local data in order to monitor make a campus 'smart'. In particular, our system infers the activities performed by users (e.g., students) in a campus in order …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionieducation.field_of_studyParticipatory sensingMultimediaComputer sciencePopulationBehavioral pattern020206 networking & telecommunications02 engineering and technologyHuman Activity Recognition Participatory Sensing Smart Campus Smart Environmentscomputer.software_genreWork (electrical)Order (business)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSmart campuseducationcomputer5G2018 IEEE International Conference on Smart Computing (SMARTCOMP)
researchProduct

Mathematical Patterns and Cognitive Architectures

2014

Mathematical patterns are an important subclass of the class of patterns. The main task of this paper is examining a particular proposal concerning the nature of mathematical patterns and some elements of the cognitive architecture an agent should have to recognize them.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimathematical patterns neural networks conceptual spaces systems of representationSettore M-FIL/02 - Logica E Filosofia Della Scienza
researchProduct

Model

2020

The term model is polysemous. It refers to concrete objects, which are chosen or made through the techniques of arts, crafts, and engineering, as well as to abstract constructions, which are built by formal, theoretical, and statistical means for descriptive, explanatory, and normative aims. The term is also extended to the effective procedure by which scientific activity may be carried out according to rules, by which it can be considered valid in order to provide knowledge.

Settore M-FIL/04 - Esteticamodeling engineering art pattern logic structureSettore M-FIL/05 - Filosofia E Teoria Dei Linguaggi
researchProduct