Search results for "saliency"

showing 10 items of 41 documents

Visual saliency detection in colour images based on density estimation

2017

International audience; A simple and effective method for visual saliency detection in colour images is presented. The method is based on the common observation that local salient regions exhibit distinct geometric and and texture patterns from neighbouring regions. We model the colour distribution of local image patches with a Gaussian density and measure the saliency of each patch as the statistical distance from that density. Experimental results with public datasets and comparison with other state-of-the-art methods show the effectiveness of our method.

0209 industrial biotechnologybusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionGaussian density02 engineering and technologyDensity estimation[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Measure (mathematics)Texture (geology)020901 industrial engineering & automationSalientComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessComputingMethodologies_COMPUTERGRAPHICSVisual saliencyElectronics Letters
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Combining Top-down and Bottom-up Visual Saliency for Firearms Localization

2014

Object detection is one of the most challenging issues for computer vision researchers. The analysis of the human visual attention mechanisms can help automatic inspection systems, in order to discard useless information and improving performances and efficiency. In this paper we proposed our attention based method to estimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanisms are involved in our system. The bottom-up analysis is based on a state-of-the-art approach. The top-down analysis is based on the construction of a probabilistic model of the firearms position with respect to the people’s face position. This model has been created by analyzi…

Firearms Detection Visual Saliency Probabilistic Model.Computer sciencebusiness.industryStatistical modelTop-down and bottom-up designObject detectionPosition (vector)Face (geometry)Visual attentionComputer visionArtificial intelligencebusinessVisual saliencyProceedings of the 11th International Conference on Signal Processing and Multimedia Applications
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On Spatio-Temporal Saliency Detection in Videos using Multilinear PCA

2016

International audience; Visual saliency is an attention mechanism which helps to focus on regions of interest instead of processing the whole image or video data. Detecting salient objects in still images has been widely addressed in literature with several formulations and methods. However, visual saliency detection in videos has attracted little attention, although motion information is an important aspect of visual perception. A common approach for obtaining a spatio-temporal saliency map is to combine a static saliency map and a dynamic saliency map. In this paper, we extend a recent saliency detection approach based on principal component analysis (PCA) which have shwon good results wh…

Multilinear mapVisual perceptiondynamic scenesComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]050105 experimental psychologyImage (mathematics)visual saliencympca[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Salience (neuroscience)0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesComputer visionSaliency mapbusiness.industry05 social sciences[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionVisualizationKadir–Brady saliency detectorPrincipal component analysis020201 artificial intelligence & image processingArtificial intelligencebusinessFocus (optics)
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Primitives detection by a discrete and non linear approach : application to the detection and caracterization of interest points for 3D meshes

2010

This manuscript is dedicated to the detection and caracterization of interest points for 3D meshes. First of all, we show the limitations of the curvature measure on sharp edges, the measure usually used for the analysis of meshes. Then, we present a generalization of the SUSAN operator for meshes, named SUSAN-3D. The saliency measure proposed quantify the local variation of the surface and classify directly the analysed vertices in five classes: salient, crest, flat, valley and cavity. The meshes under consideration are manifolds and can be closed or non-closed, regulars or irregulars, dense or not and noised or not. The accuracy of the SUSAN-3D operator is compared to two curvature operat…

Saliency[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]Irregular meshes[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]CaracterizationAnalyse multi-échelle[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Multi-scale analysisSaillance[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Salient pointsDétectionDetection[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]Maillages irréguliersCaractérisationPoints saillants[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]Points d'intérêtInterest points
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Study and Comparison of Surface Roughness Measurements

2014

Journées du Groupe de Travail en Modélisation Géométrique (GTMG'14), Lyon; This survey paper focus on recent researches whose goal is to optimize treatments on 3D meshes, thanks to a study of their surface features, and more precisely their roughness and saliency. Applications like watermarking or lossy compression can benefit from a precise roughness detection, to better hide the watermarks or quantize coarsely these areas, without altering visually the shape. Despite investigations on scale dependence leading to multi-scale approaches, an accurate roughness or pattern characterization is still lacking, but challenging for those treatments. We think there is still room for investigations t…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]watermarking.quality assessmentsaliencywatermarking[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]simplificationvisual perceptionsmoothing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingfeature-preservingcompression[ PHYS.PHYS.PHYS-DATA-AN ] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]multi-scale analysisvisual masking3D mesh[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an][PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an][ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]roughness[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Maximum Torque per Ampere Control strategy for low-saliency ratio IPMSMs

2019

This paper deals with electrical drives employing low-saliency ratio interior permanent magnet synchronous motors. In particular, in order to help the designers choosing the best control algorithm, the performances of the Maximum Torque Per Ampere Control (MTPA) and the Field Orientation Control (FOC) are here both theoretically and experimentally assessed and compared, by using, as performance indicators, the torque-current ratio and the power losses. The tests are carried out on a low-power motor for various speeds and loads by implementing the two control strategies in a dSPACE® rapid prototyping system. The results show that the Maximum Torque Per Ampere algorithm has some appreciable a…

Low saliency ratio machineMTPA control strategySettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciFOC algorithmSettore ING-INF/07 - Misure Elettriche E ElettronicheIPMSM
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A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

2020

In the first seconds of observation of an image, several visual attention processes are involved in the identification of the visual targets that pop-out from the scene to our eyes. Saliency is the quality that makes certain regions of an image stand out from the visual field and grab our attention. Saliency detection models, inspired by visual cortex mechanisms, employ both colour and luminance features. Furthermore, both locations of pixels and presence of objects influence the Visual Attention processes. In this paper, we propose a new saliency method based on the combination of the distribution of interest points in the image with multiscale analysis, a centre bias module and a machine …

General Computer ScienceComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONinterest pointsLuminanceSalience (neuroscience)medicineVisual attentionGeneral Materials ScienceComputer visionElectrical and Electronic EngineeringVisual saliencySettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelbusiness.industryGeneral EngineeringEye-movementsObject (computer science)saliency mapVisual fieldIdentification (information)Visual cortexmedicine.anatomical_structurevisual attentionEye trackinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligenceScale (map)businesslcsh:TK1-9971
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Saliency Map for Visual Perception

2015

Human and other primates move their eyes to select visual information from the scene, psycho-visual experiments (Constantinidis, 2005) suggest that attention is directed to visually salient locations in the image. This allows human beings to bring the fovea onto the relevant parts of the image, to interpret complex scenes in real time. In visual perception, an important result was the discovery of a limited set of visual properties (called pre attentive), detected in the first 200-300 milliseconds of observation of a scene, by the low-level visual system. In last decades many progresses have been made into research of visual perception by analyzing both bottom up (stimulus driven) and top d…

Visual saliencyVisual perceptionSaliency maps.Visual perception; Visual saliency; Saliency maps.
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Physical Metaphor for Streaming Media Retargeting

2014

We here introduce an image/video retargeting method that operates arbitrary aspect ratios resizing achieved in real-time performances. Most of the literature retargeting approaches sacrifice real-time performances in behalf of quality. On the other hand, existing fast methods provide arguable results. We can obtain a valuable trade-off between effectiveness and efficiency. The method named Spring Simulation Retargeting (SSR) is mainly based on a physical springs-based simulation. The media are assumed as flexible objects composed of particles and springs with different local stiffness properties, related to the visual importance of the content. The variation of the object size generates ela…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryVariation (game tree)Object (computer science)Computer Science ApplicationsVisualizationImage (mathematics)Spring (device)Computer graphics (images)Signal ProcessingRetargetingMedia TechnologyComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessPhysical simulation retargeting visual saliency
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Context-Aware Model Applied to Hog Descriptor for People Detection

2018

International audience; This work proposes and implements a method based on Context-Aware Visual Attention Model (CAVAM), but modifying the method in such way that the detection algorithm is replaced by Histograms of Oriented Gradients (HOG). After reviewing different algorithms for people detection, we select HOG method because it is a very well known algorithm, which is used as a reference in virtually all current research studies about automatic detection. In addition, it produces accurate results in significantly less time than many algorithms. In this way, we show that CAVAM model can be adapted to other methods for object detection besides Scale-Invariant Feature Transform (SIFT), as …

[SPI]Engineering Sciences [physics]Object detectionsaliency[SPI] Engineering Sciences [physics]pedestrian detectiontile-based methodregions of interest
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