Search results for "DETECT"

showing 10 items of 5902 documents

Real-Time Hand Pose Recognition Based on a Neural Network Using Microsoft Kinect

2013

The Microsoft Kinect sensor is largely used to detect and recognize body gestures and layout with enough reliability, accuracy and precision in a quite simple way. However, the pretty low resolution of the optical sensors does not allow the device to detect gestures of body parts, such as the fingers of a hand, with the same straightforwardness. Given the clear application of this technology to the field of the user interaction within immersive multimedia environments, there is the actual need to have a reliable and effective method to detect the pose of some body parts. In this paper we propose a method based on a neural network to detect in real time the hand pose, to recognize whether it…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtificial neural networkgesture recognitionbusiness.industryComputer scienceMicrosoft Kinect.gesture-based interactionVirtual realityObject detectionhuman-computer interactionFeature (computer vision)Gesture recognitionComputer visionArtificial intelligenceNoise (video)businessPoseGesture2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications
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A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing

2021

Vehicular Social Networks (VSNs) is an emerging communication paradigm, derived by merging the concepts of Online Social Networks (OSNs) and Vehicular Ad-hoc Networks (VANETs). Due to the lack of robust authentication mechanisms, social-based vehicular applications are vulnerable to numerous attacks including the generation of sybil entities in the networks. We address this important issue in vehicular crowdsourcing campaigns where sybils are usually employed to increase their influence and worsen the functioning of the system. In particular, we propose a novel User Recruitment Policy (URP) that, after extracting the participants within the event radius of a crowdsourcing campaign, detects …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniAuthenticationEvent (computing)business.industryComputer sciencecomputer.internet_protocolComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSCrowdsourcingComputer securitycomputer.software_genreDomain (software engineering)Random forestCrowdsourcing; Proximity Graph; Sybil detection; Trust and Truthfulness; Vehicular Social NetworkCrowdsourcing Proximity Graph Sybil detection Trust and Truthfulness Vehicular Social NetworkGraph (abstract data type)RADIUSbusinesscomputer
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Blood vessels and feature points detection on retinal images

2009

In this paper we present a method for the automatic extraction of blood vessels from retinal images, while capturing points of intersection/overlap and endpoints of the vascular tree. The algorithm performance is evaluated through a comparison with handmade segmented images available on the STARE project database (STructured Analysis of the REtina). The algorithm is performed on the green channel of the RGB triad. The green channel can be used to represent the illumination component. The matched filter is used to enhance vessels w.r.t. the background. The separation between vessels and background is accomplished by a threshold operator based on gaussian probability density function. The len…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniChannel (digital image)Pixelbusiness.industryMatched filterGaussianRetinal VesselsSensitivity and SpecificityRetinaIntersection (Euclidean geometry)Pattern Recognition AutomatedTree (data structure)symbols.namesakevessels feature detectionFeature (computer vision)Image Interpretation Computer-AssistedsymbolsHumansRGB color modelComputer visionArtificial intelligencebusinessAlgorithmsMathematics2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Clifford Algebra based Edge Detector for Color Images

2012

Edge detection is one of the most used methods for feature extraction in computer vision applications. Feature extraction is traditionally founded on pattern recognition methods exploiting the basic concepts of convolution and Fourier transform. For color image edge detection the traditional methods used for gray-scale images are usually extended and applied to the three color channels separately. This leads to increased computational requirements and long execution times. In this paper we propose a new, enhanced version of an edge detection algorithm that treats color value triples as vectors and exploits the geometric product of vectors defined in the Clifford algebra framework to extend …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniColor imagebusiness.industryComputer scienceColor image edge detectionClifford convolutionFeature extractionClifford algebraEdge detectionConvolutionsymbols.namesakeClifford Fourier transformFourier transformsymbolsCanny edge detectorComputer visionArtificial intelligenceClifford algebrabusinessAlgorithmImage gradient
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Video object recognition and modeling by SIFT matching optimization

2014

In this paper we present a novel technique for object modeling and object recognition in video. Given a set of videos containing 360 degrees views of objects we compute a model for each object, then we analyze short videos to determine if the object depicted in the video is one of the modeled objects. The object model is built from a video spanning a 360 degree view of the object taken against a uniform background. In order to create the object model, the proposed techniques selects a few representative frames from each video and local features of such frames. The object recognition is performed selecting a few frames from the query video, extracting local features from each frame and looki…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industry3D single-object recognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONDeep-sky objectCognitive neuroscience of visual object recognitionObject Modeling Video Query Object Recognition.Object (computer science)Object-oriented designObject-class detectionVideo trackingObject modelComputer visionArtificial intelligencebusiness
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Composition of SIFT features for robust image representation

2010

In this paper we propose a novel feature based on SIFT (Scale Invariant Feature Transform) algorithm1 for the robust representation of local visual contents. SIFT features have raised much interest for their power of description of visual content characterizing punctual information against variation of luminance and change of viewpoint and they are very useful to capture local information. For a single image hundreds of keypoints are found and they are particularly suitable for tasks dealing with image registration or image matching. In this work we stretched the spatial coverage of descriptors creating a novel feature as composition of keypoints present in an image region while maintaining…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationScale-invariant feature transformartificial intelligenceLuminanceimage annotationImage (mathematics)bag of wordsFeature (computer vision)SIFTvisual termsComputer visionArtificial intelligenceAffine transformationbusinessRepresentation (mathematics)semanticsImage representationFeature detection (computer vision)
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Real-time estimation of geometrical transformation between views in distributed smart-cameras systems

2008

In this paper, we present a method to automatically estimate the geometric relations among the different views of cameras with partially overlapping fields of view in a wireless video-surveillance system. The method uses the locations of the detected moving objects visible at the same time in two or more views. The correspondences among objects are found by comparing their appearance models based on dominant colour descriptors while the geometric transformation are computed iteratively and may be used to solve the consistent labelling problem. As a significant part of the processing is performed on the smart cameras, the method has been conceived by taking into account the limited resources…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryGeometric transformationMotion detectiondistributed video surveillanceObject detectionData modelingTransformation (function)Computer visionSmart cameraArtificial intelligenceImage sensorbusinessHomography (computer vision)2008 Second ACM/IEEE International Conference on Distributed Smart Cameras
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Multidirectional Scratch Detection and Restoration in Digitized Old Images

2010

Line scratches are common defects in old archived videos, but similar imperfections may occur in printed images, in most cases by reason of improper handling or inaccurate preservation of the support. Once an image is digitized, its defects become part of that image. Many state-of-the-art papers deal with long, thin, vertical lines in old movie frames, by exploiting both spatial and temporal information. In this paper we aim to face with a more challenging and general problem: the analysis of line scratches in still images, regardless of their orientation, color, and shape. We present a detection/restoration method to process this defect.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryOrientation (computer vision)lcsh:ElectronicsProcess (computing)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-8360Image processingImage processing Scratch detectionImage restorationScratchFace (geometry)Signal ProcessingPattern recognition (psychology)Line (geometry)Computer visionArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerImage restorationInformation Systemscomputer.programming_languageImage restoration; Image processing Scratch detectionEURASIP Journal on Image and Video Processing
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Texture classification for content-based image retrieval

2002

An original approach to texture-based classification of regions, for image indexing and retrieval, is presented. The system addresses automatic macro-textured ROI detection, and classification: we focus our attention on those objects that can be characterized by a texture as a whole, like trees, flowers, walls, clouds, and so on. The proposed architecture is based on the computation of the /spl lambda/ vector from each selected region, and classification of this feature by means of a pool of suitably trained support vector machines (SVM). This approach is an extension of the one previously developed by some of the authors to classify image regions on the basis of the geometrical shape of th…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniContextual image classificationComputer sciencebusiness.industryFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionImage segmentationContent-based image retrievalCBIR texture analysisObject detectionImage textureFeature (computer vision)Computer visionArtificial intelligencebusinessImage retrievalProceedings 11th International Conference on Image Analysis and Processing
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A tool to support the creation of datasets of tampered videos

2015

Digital Video Forensics is getting a growing interest from the Multimedia research community, as the need for methods to validate the authenticity of a video content is increasing with the number of videos freely available to the digital users. Unlike Digital Image Forensics, to our knowledge, there are not standard datasets to test video forgery detection techniques. In this paper we present a new tool to support the users in creating datasets of tampered videos. We furthermore present our own dataset and we discuss some remarks about how to create forgeries difficult to be detected by an observer, to the naked eye.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCopy move forgeryCopy move forgeryInformation retrievalVideo forensicComputer scienceForgery detectionComputer Science (all)Digital videoComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONObject trackingCopy move forgery; Object tracking; Video forensics; Computer Science (all); Theoretical Computer ScienceData scienceTheoretical Computer ScienceVideo trackingResearch communityDigital image forensics
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