Search results for "computer vision"

showing 10 items of 2353 documents

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
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A Programmable Networked Processing Node for 3D Brain Vessels Reconstruction

2011

Real-time 3D imaging represents a developing trend in medical imaging. However, most of the 3D medical imaging algorithms are computationally intensive. In this paper, a programmable networked node for 3D brain vessels reconstruction is proposed. Starting from 2D PC-MRA (Phase-Contrast Magnetic Resonance Angiography) sequences, the node is able to generate the 3D brain vasculature using the MIP (Maximum Intensity Projection) algorithm. The node has been prototyped on the Celoxica RC203E board, equipped with a Virtex II FPGA, to get the advantages of an hardware implementation, reaching a better throughput with respect to analogous software implementations. Its generality and programmable ca…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniVirtexbusiness.industryComputer scienceNode (networking)Iterative reconstructionDICOMMaximum intensity projectionMedical imagingMedical data processing 3D Brain Vessels Reconstruction embedded FPGA-based deviceComputer visionArtificial intelligenceField-programmable gate arraybusinessThroughput (business)Computer hardware
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Saliency Based Image Cropping

2013

Image cropping is a technique that is used to select the most relevant areas of an image, discarding the useless ones. Handmade selection, especially in case of large photo collections, is a time consuming task. Automatic image cropping techniques may help users, suggesting to them which part of the image is the most relevant, according to specific criteria. We suppose that the most visually salient areas of a photo are also the most relevant ones to the users. In this paper we present an extended version of our previously proposed method, to extract the saliency map of an image, which is based on the analysis of the distribution of the interest points of the image. Three different interest…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniVisual perceptionPoint (typography)business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTask (project management)Image (mathematics)SalientSelection (linguistics)Computer visionState (computer science)Artificial intelligencebusinessCroppingImage Cropping Visual Saliency Visual Perception Saliency Map
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Combining textual and visual cues for content-based image retrieval on the World Wide Web

2002

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 (LSI) 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 report…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniWorld Wide WebInformation retrievalIndex (publishing)Distributed databaseOrientation (computer vision)Computer scienceHistogramSearch engine indexingContent-based image retrievalSensory cueImage retrievalCBIR latent semantic indexingProceedings. IEEE Workshop on Content-Based Access of Image and Video Libraries (Cat. No.98EX173)
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360° Tracking Using a Virtual PTZ Camera

2017

Object tracking using still or PTZ cameras is a hard task for large spaces and needs several devices to completely cover the area or to track multiple subjects. The introduction of \(360^{\circ }\) camera technology offers a complete view of the scene in a single image and can be useful to reduce the number of devices needed in the tracking problem. In this paper we present a framework using \(360^{\circ }\) cameras to simulate an unlimited number of PTZ cameras and to be used for tracking. The proposed method to track a single target process an equirectangular view of the scene and obtains a model of the moving object in the image plane. The target is tracked analyzing the next frame of th…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceComputer Science (all)Frame (networking)360 cameraComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Center (category theory)02 engineering and technologyObject trackingImage planeTracking (particle physics)Theoretical Computer ScienceCover (topology)020204 information systemsVideo trackingPTZ camera0202 electrical engineering electronic engineering information engineeringEquirectangular projection020201 artificial intelligence & image processingComputer visionEquirectangular projectionArtificial intelligencebusiness
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Midground Object Detection in Real World Video Scenes,

2007

Traditional video scene analysis depends on accurate background modeling to identify salient foreground objects. However, in many important surveillance applications, saliency is defined by the appearance of a new non-ephemeral object that is between the foreground and background. This midground realm is defined by a temporal window following the object's appearance; but it also depends on adaptive background modeling to allow detection with scene variations (e.g., occlusion, small illumination changes). The human visual system is ill-suited for midground detection. For example, when surveying a busy airline terminal, it is difficult (but important) to detect an unattended bag which appears…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScene statisticsObject (computer science)Object detectionObject-class detectionComputational efficiencyComputer networksSalientVideo trackingHuman visual system modelComputer visionViola–Jones object detection frameworkArtificial intelligencebusiness
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Text localization from photos

2009

In this paper a new text extraction algorithm is proposed. In real scenes the text is usually overlapped or is part of the background. To identify the text regions, in complex conditions, a method exploiting a “multi-resolution feature based method” for extracting text with undefined dimension has been developed. Once identified, the multi-resolution information are merged and skimmed through a set of Support Vector Machines (SVM). The tests and the comparisons with other techniques, performed on heterogeneous images, have shown the effectiveness of the proposed.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceFeature extractionPattern recognitionSupport vector machineSet (abstract data type)Text Localization Image UnderstandingDimension (vector space)Pattern recognition (psychology)Computer visionArtificial intelligencebusinessImage resolution2009 Digest of Technical Papers International Conference on Consumer Electronics
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Multimodal Mean Adaptive Backgrounding for Embedded Real-Time Video Surveillance

2007

Automated video surveillance applications require accurate separation of foreground and background image content. Cost sensitive embedded platforms place realtime performance and efficiency demands on techniques to accomplish this task. In this paper we evaluate pixel-level foreground extraction techniques for a low cost integrated surveillance system. We introduce a new adaptive technique, multimodal mean (MM), which balances accuracy, performance, and efficiency to meet embedded system requirements. Our evaluation compares several pixel-level foreground extraction techniques in terms of their computation and storage requirements, and functional accuracy for three representative video sequ…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMixture modelReduction (complexity)TRACKINGReal time videoTask (computing)BackgroundingComputer visionArtificial intelligencebusiness2007 IEEE Conference on Computer Vision and Pattern Recognition
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Mean shift clustering for personal photo album organization

2008

In this paper we propose a probabilistic approach for the automatic organization of pictures in personal photo album. Images are analyzed in term of faces and low-level visual features of the background. The description of the background is based on RGB color histogram and on Gabor filter energy accounting for texture information. The face descriptor is obtained by projection of detected and rectified faces on a common low dimensional eigenspace. Vectors representing faces and background are clustered in an unsupervised fashion exploiting a mean shift clustering technique. We observed that, given the peculiarity of the domain of personal photo libraries where most of the pictures contain fa…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionFacial recognition systemVisualizationComputingMethodologies_PATTERNRECOGNITIONGabor filterImage textureCBIR image analysis image clusteringHistogramRGB color modelComputer visionMean-shiftArtificial intelligencebusinessFace detectionMathematics
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Exponential Entropy Driven HUM on Knee MR Images

2007

A very important artifact corrupting Magnetic Resonance Images is the RF inhomogeneity. This kind of artifact generates variations of illumination which trouble both direct examination by the doctor and segmentation algorithms. Even if homomorphic filtering approaches have been presented in literature, none of them has developed a measure to determine the cut-off frequency. In this work we present a measure based on information theory with a large experimental setup aimed to demonstrate the validity of our approach.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryEntropy Knee Magnetic resonance rf-inhomogeneityImage segmentationInformation theoryExponential functionHomomorphic filteringHumEntropy (information theory)SegmentationComputer visionArtificial intelligenceMr imagesbusinessMathematics2005 IEEE Engineering in Medicine and Biology 27th Annual Conference
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