Search results for "Computer Vision"

showing 10 items of 2353 documents

Introducing Pseudo-Singularity Points for Efficient Fingerprints Classification and Recognition

2010

Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Generally, fingerprint recognition is based on a set of relevant local characteristics, such as ridge ending and bifurcation (minutiae). Fingerprint classification is based on fingerprint global features, such as core and delta singularity points. Unfortunately, singularity points are not always present in a fingerprint image: the acquisition process is not ideal, so that the fingerprint is broken, or the fingerprint belongs to the arch class. In the above cases, pseudo-singularity-points will be detected and extracted to make possible fingerprint classification and matching. As result, fingerpr…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMinutiaeContextual image classificationbusiness.industryComputer scienceData_MISCELLANEOUSFeature extractionFingerprint Verification CompetitionPattern recognitionFingerprint recognitionFingerprint singularity regions classification matching algorithm core and delta points fingerprint recognition systems.Statistical classificationFingerprintData_GENERALComputer visionArtificial intelligencebusinessBlossom algorithm2010 International Conference on Complex, Intelligent and Software Intensive Systems
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Multi-modal Medical Image Registration by Local Affine Transformations

2018

Image registration is the process of finding the geometric transformation that, applied to the floating image, gives the registered image with the highest similarity to the reference image. Registering a pair of images involves the definition of a similarity function in terms of the parameters of the geometric transformation that allows the registration. This paper proposes to register a pair of images by iteratively maximizing the empirical mutual information through coordinate gradient descent. Hence, the registered image is obtained by applying a sequence of local affine transformations. Rather than adopting a uniformly spaced grid to select image blocks to locally register, as done by s…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniModalbusiness.industryComputer scienceImage Registration Mutual Information Medical ImagesImage registrationComputer visionArtificial intelligenceAffine transformationbusiness
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A Multimodal People Recognition System for an Intelligent Environment

2011

In this paper, a multimodal system for recognizing people in intelligent environments is presented. Users are identified and tracked by detecting and recognizing voices and faces through cameras and microphones spread around the environment. This multimodal approach has been chosen to develop a flexible and cheap though reliable system, implemented through consumer electronics. Voice features are extracted through a short time spectrum analysis, while face features are extracted using the eigenfaces technique. The recognition task is achieved through the use of some Support Vector Machines, one per modality, that learn and classify the features of each person, while bindings between modalit…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniModality (human–computer interaction)Intelligent EnviromentMultimodal Recognition SystemComputer sciencebusiness.industrySupport vector machineSoftwareEigenfaceMiddlewareLearning ruleIntelligent environmentComputer visionArtificial intelligencebusiness
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Video Indexing Using MPEG Motion Compensation Vectors

2003

In the last years a lot of work has been done on color, textural, structural and semantic indexing of "content-based" video databases. Motion-based video indexing has been less explored, with approaches generally based on the analysis of optical flows. Compressed videos require the decompression of the sequences and the computation of optical flows, two steps computationally heavy. In this paper we propose some methods to index videos by motion features (mainly related to camera motion) and by motion-based spatial segmentation of frames, in a fully automatic way. Our idea is to use MPEG motion vectors as an alternative to optical flows. Their extraction is very simple and fast; it doesn't r…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMotion analysisMotion compensationComputer sciencebusiness.industrySearch engine indexingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage segmentationMotion vectorQuarter-pixel motionVideo indexing motion analysisMotion estimationComputer Science::MultimediaComputer visionArtificial intelligencebusinessBlock-matching algorithm
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Video indexing using optical flow field

2002

The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of digital video. Several content based features (color, texture, motion, etc.) are needed to perform a reliable content based retrieval. We present a method for automatic motion based video indexing and retrieval. A prototypal system has been developed to prove the validity of our approach. Our system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes some motion based features related to the optical flow field. Motion based queries are then performed either in a quali…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMotion compensationbusiness.industryComputer scienceSearch engine indexingDigital videoFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowImage segmentationVideo processingElectronic mailVideo indexing motion analysisMotion estimationComputer visionArtificial intelligencebusinessBlock-matching algorithm
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Enabling Technologies on Hybrid Camera Networks for Behavioral Analysis of Unattended Indoor Environments and Their Surroundings

2008

This paper presents a layered network architecture and the enabling technologies for accomplishing vision-based behavioral analysis of unattended environments. Specifically the vision network covers both the attended environment and its surroundings by means of multi-modal cameras. The layer overlooking at the surroundings is laid outdoor and tracks people, monitoring entrance/exit points. It recovers the geometry of the site under surveillance and communicates people positions to a higher level layer. The layer monitoring the unattended environment undertakes similar goals, with the addition of maintaining a global mosaic of the observed scene for further understanding. Moreover, it merges …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniNetwork architecturebusiness.industryReliability (computer networking)Computer laboratorydistributed video surveillanceSMART CAMERA NETWORKSBehavioral analysisMULTI-MODAL SENSOR FUSIONECamera networkGeographyHuman–computer interactionmulti-modal surveillance; wireless sensor networksEMBEDDED SMART CAMERASmulti-modal surveillanceMULTI-MODAL SENSOR FUSIONE; SMART CAMERA NETWORKS; EMBEDDED SMART CAMERASComputer visionArtificial intelligenceLayer (object-oriented design)businesswireless sensor networks
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Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion

2008

This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction, This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniNoise Removal Magnetic Resonance Images Anisotropic Diffusion Brain MRIDiffusion equationNoise measurementComputer scienceAnisotropic diffusionWiener filterComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFilter (signal processing)Edge-preserving smoothingMagnetic fieldAdaptive filtersymbols.namesakeComputer Science::Computer Vision and Pattern RecognitionsymbolsAlgorithm2008 21st IEEE International Symposium on Computer-Based Medical Systems
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Real-Time Object Detection in Embedded Video Surveillance Systems

2008

In this paper we report a new method to detect both moving objects and new stationary objects in video sequences. On the basis of temporal consideration we classify pixels into three classes: background, midground and foreground to distinguish between long-term, medium-term and short-term changes. The algorithm has been implemented on a hardware platform with limited resources and it could be used in a wider system like a wireless sensor networks. Particular care has been put in realizing the algorithm so that the limited available resources are used in an efficient way. Experiments have been conducted on publicly available datasets and performance measures are reported.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelBasis (linear algebra)business.industryComputer scienceReal-time computingVideo sequencevideo surveillance embedded systemsObject detectionTerm (time)Statistical classificationComputer visionArtificial intelligencebusinessWireless sensor networkLimited resources2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
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Pedestrian Tracking in 360 Video by Virtual PTZ Cameras

2018

Since the data acquired by a PTZ camera change while adjusting the pan, tilt and zoom parameters, the results of tracking algorithms are difficult to reproduce; such diffi- culty limits the development and the comparison of tracking algorithms with PTZ cameras. The recently introduced 360- degree cameras acquire spherical views of the environment, generally stored as equirectangular images. Each pixel of an equirectangular image corresponds to a point on the spherical surface. A gnomonic projection can be used to project the points on the spherical surface onto a plane tangent to the sphere. Such tangent plane can be interpreted as the image plane of a virtual PTZ camera oriented towards th…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage planeTracking (particle physics)Gnomonic projectionAppearance models Dynamic memory Pedestrian tracking Spherical surface Tracking algorithm Tracking by detections Virtual cameraComputer Science::Computer Vision and Pattern RecognitionEquirectangular projectionComputer visionDevelopment (differential geometry)Artificial intelligenceZoombusinessTilt (camera)2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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Restoration of Digitized Damaged Photos using Bit-Plane Slicing

2007

Digital image restoration aims to recover damaged zones of a digital image, using surrounding information. In this paper we propose a novel approach, based on bit-plane slicing decomposition, with the purpose to make information analysis and reconstruction process easy, fast and effective. Tests have been made on digitized damaged old photos to restore several classes of typical defects in old photographic prints.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Image processingIterative reconstructionDigital imageImage restorationComputer graphics (images)Computer visionArtificial intelligenceBit plane slicingbusinessImage restorationBit-plane slicing Digital inpainting Image restoration
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