Search results for "Computer Vision and Pattern Recognition"

showing 10 items of 997 documents

Improving Harris corner selection strategy

2011

This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors' approa…

Settore INF/01 - Informaticabusiness.industryAutocorrelationDetectorCorner detectionGeometryScale invarianceEdge detectionAutocorrelation matrixComputer Vision and Pattern RecognitionArtificial intelligenceInvariant (mathematics)Linear combinationbusinessAlgorithmSoftwareMathematicsHarris corner detector
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Cross-Technology WiFi/ZigBee Communications: Dealing With Channel Insertions and Deletions

2016

In this letter, we show how cross-technology interference can be exploited to set up a low-rate bidirectional communication channel between heterogeneous WiFi and ZigBee networks. Because of the environment noise and receivers' implementation, the cross-technology channel can be severely affected by insertions and deletions of symbols, whose effects need to be taken into account by the coding scheme and communication protocol.

Settore ING-INF/03 - TelecomunicazioniComputer sciencebusiness.industryWiFichannelinterferencewireless coexistenceComputer Science Applications1707 Computer Vision and Pattern Recognition020206 networking & telecommunications020302 automobile design & engineeringinterference; wireless coexistence; WLAN; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering02 engineering and technologyComputer Science ApplicationsWLANZigBee0203 mechanical engineeringModeling and Simulation0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringbusinessCommunications protocolComputer networkCommunication channelIEEE Communications Letters
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A New Preclinical Decision Support System Based on PET Radiomics: A Preliminary Study on the Evaluation of an Innovative 64Cu-Labeled Chelator in Mou…

2022

The 64Cu-labeled chelator was analyzed in vivo by positron emission tomography (PET) imaging to evaluate its biodistribution in a murine model at different acquisition times. For this purpose, nine 6-week-old female Balb/C nude strain mice underwent micro-PET imaging at three different time points after 64Cu-labeled chelator injection. Specifically, the mice were divided into group 1 (acquisition 1 h after [64Cu] chelator administration, n = 3 mice), group 2 (acquisition 4 h after [64Cu]chelator administration, n = 3 mice), and group 3 (acquisition 24 h after [64Cu] chelator administration, n = 3 mice). Successively, all PET studies were segmented by means of registration with a standard te…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni64radiomics; micro-PET/CT; mouse imaging; atlas; <sup>64</sup>Cu-labeled chelatorCu-labeled chelatormicro-PET/CTComputer Graphics and Computer-Aided Design64Cu-labeled chelatoratlaradiomicsRadiology Nuclear Medicine and imagingatlasmouse imagingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringRadiomic64; Cu-labeled chelator; atlas; micro-PET/CT; mouse imaging; radiomicsradiomics; micro-PET/CT; mouse imaging; atlas; 64Cu-labeled chelator J.Journal of Imaging; Volume 8; Issue 4; Pages: 92
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A multi‐agent system for itinerary suggestion in smart environments

2021

Abstract Modern smart environments pose several challenges, among which the design of intelligent algorithms aimed to assist the users. When a variety of points of interest are available, for instance, trajectory recommendations are needed to suggest users the most suitable itineraries based on their interests and contextual constraints. Unfortunately, in many cases, these interests must be explicitly requested and their lack causes the so‐called cold‐start problem. Moreover, lengthy travelling distances and excessive crowdedness of specific points of interest make itinerary planning more difficult. To address these aspects, a multi‐agent itinerary suggestion system that aims at assisting t…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtificial intelligenceComputer Networks and CommunicationsComputer scienceMulti-agent systemDistributed computingpattern recognitionHuman-Computer InteractionQA76.75-76.765Computational linguistics. Natural language processingSmart environmentComputer softwareComputer Vision and Pattern RecognitionP98-98.5Information Systems
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A knowledge based architecture for the virtual restoration of ancient photos

2017

Abstract Historical images are essential documents of the recent past. Nevertheless, time and bad preservation corrupt their physical supports. Digitization can be the solution to extend their “lives”, and digital techniques can be used to recover lost information. This task is often difficult and time-consuming, if commercial restoration tools are used for the purpose. A new solution is proposed to help non-expert users in restoring their damaged photos. First, we defined a dual taxonomy for the defects in printed and digitized photos. We represented our restoration domain with an ontology and we created some rules to suggest actions to perform in case of some specific events. Classes and …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryProcess (engineering)Interface (Java)020206 networking & telecommunications02 engineering and technologyOntology (information science)Task (project management)Domain (software engineering)World Wide WebImage restoration Historical photos Digitization Ontology Knowledge baseKnowledge baseArtificial IntelligenceSignal Processing0202 electrical engineering electronic engineering information engineeringWeb application020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionbusinessImage restoration Historical photos Digitization Ontology Knowledge baseSoftwareDigitizationPattern Recognition
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State of the art in passive digital image forgery detection: copy-move image forgery

2017

Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is cop…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCopyingCopy-move forgery Digital forensics Duplicated detection Manipulation detectionbusiness.industryComputer sciencemedia_common.quotation_subjectDigital forensicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020207 software engineering02 engineering and technologyImage (mathematics)Digital imageArtificial IntelligenceOriginalityPattern recognition (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionRelevance (information retrieval)Computer Vision and Pattern RecognitionArtificial intelligenceState (computer science)businessmedia_commonPattern Analysis and Applications
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HarrisZ$^+$: Harris Corner Selection for Next-Gen Image Matching Pipelines

2022

Due to its role in many computer vision tasks, image matching has been subjected to an active investigation by researchers, which has lead to better and more discriminant feature descriptors and to more robust matching strategies, also thanks to the advent of the deep learning and the increased computational power of the modern hardware. Despite of these achievements, the keypoint extraction process at the base of the image matching pipeline has not seen equivalent progresses. This paper presents HarrisZ$^+$, an upgrade to the HarrisZ corner detector, optimized to synergically take advance of the recent improvements of the other steps of the image matching pipeline. HarrisZ$^+$ does not onl…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFOS: Computer and information sciencesHarris detectorSettore INF/01 - InformaticaComputer Vision and Pattern Recognition (cs.CV)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputer Science - Computer Vision and Pattern Recognitionlocal featurecorner detectorArtificial IntelligenceSignal Processingkeypoint detectorStructure-from-MotionComputer Vision and Pattern RecognitionHarrisZSoftware
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3D skeleton-based human action classification: A survey

2016

In recent years, there has been a proliferation of works on human action classification from depth sequences. These works generally present methods and/or feature representations for the classification of actions from sequences of 3D locations of human body joints and/or other sources of data, such as depth maps and RGB videos.This survey highlights motivations and challenges of this very recent research area by presenting technologies and approaches for 3D skeleton-based action classification. The work focuses on aspects such as data pre-processing, publicly available benchmarks and commonly used accuracy measurements. Furthermore, this survey introduces a categorization of the most recent…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalBody pose representationPoint (typography)Computer science020207 software engineering02 engineering and technologySkeleton (category theory)computer.software_genreAction recognitionField (computer science)Action classificationAction (philosophy)CategorizationArtificial IntelligenceBody jointSignal Processing0202 electrical engineering electronic engineering information engineeringFeature (machine learning)020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionData miningcomputerSkeletonSoftwarePattern Recognition
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Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web

1999

A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are reported for…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalComputer scienceOrientation (computer vision)Search engine indexingHTMLSemanticsContent-based image retrievalCBIR latent semantic indexingWorld Wide WebIndex (publishing)HistogramSignal ProcessingComputer Vision and Pattern RecognitionSensory cuecomputerSoftwarecomputer.programming_language
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An on-line learning method for face association in personal photo collection

2012

Due to the widespread use of cameras, it is very common to collect thousands of personal photos. A proper organization is needed to make the collection usable and to enable an easy photo retrieval. In this paper, we present a method to organize personal photo collections based on ''who'' is in the picture. Our method consists in detecting the faces in the photo sequence and arranging them in groups corresponding to the probable identities. This problem can be conveniently modeled as a multi-target visual tracking where a set of on-line trained classifiers is used to represent the identity models. In contrast to other works where clustering methods are used, our method relies on a probabilis…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalComputer sciencebusiness.industrySemi-supervised learningUSableDigital libraryMachine learningcomputer.software_genreSet (abstract data type)Face descriptor Data association On-line learning Semi-supervised learning Digital librariesFace (geometry)Signal ProcessingIdentity (object-oriented programming)Eye trackingComputer Vision and Pattern RecognitionArtificial intelligencebusinessCluster analysiscomputer
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