Search results for "Visual saliency"

showing 10 items of 23 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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Convolutional Neural Network for Blind Mesh Visual Quality Assessment Using 3D Visual Saliency

2018

In this work, we propose a convolutional neural network (CNN) framework to estimate the perceived visual quality of 3D meshes without having access to the reference. The proposed CNN architecture is fed by small patches selected carefully according to their level of saliency. To do so, the visual saliency of the 3D mesh is computed, then we render 2D projections from the 3D mesh and its corresponding 3D saliency map. Afterward, the obtained views are split to obtain 2D small patches that pass through a saliency filter to select the most relevant patches. Experiments are conducted on two MVQ assessment databases, and the results show that the trained CNN achieves good rates in terms of corre…

Computer sciencebusiness.industryQuality assessmentDistortion (optics)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020207 software engineeringPattern recognition02 engineering and technologyFilter (signal processing)Convolutional neural networkVisualizationSalience (neuroscience)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSaliency mapArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICSVisual saliency2018 25th IEEE International Conference on Image Processing (ICIP)
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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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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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Image Quality Assessment by saliency maps

2012

Image Quality Assessment (IQA) is an interesting challenge for image processing applications. The goal of IQA is to replace human judgement of perceived image quality with a machine evaluation. A large number of methods have been proposed to evaluate the quality of an image which may be corrupted by noise, distorted during acquisition, transmission, compression, etc. Many methods, in some cases, do not agree with human judgment because they are not correlated with human visual perception. In the last years the most modern IQA models and metrics considered visual saliency as a fundamental issue. The aim of visual saliency is to produce a saliency map that replicates the human visual system (…

Image Quality Assessment Visual Saliency Saliency Map Human Visual System Perceptual Quality
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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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Browser independent content based image resizing for liquid web layouts

2010

A typical problem for webdesigners is to realize pages that can be potentially accessed from a number of display devices with different screen sizes and resolutions. Liquid layouts can help for this purpose. However, they can not typically be applied to images, which need to be rescaled or deformed. In both cases usability could be deteriorated. Content-aware image resizing techniques can help for this goal by rescaling the images to the desired width while preserving important image structures. This paper presents a content-aware resizing technique which can be seamlessly integrated into web pages without any effort from the user. The results from the system application prove its effective…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputerApplications_COMPUTERSINOTHERSYSTEMSUsabilityImage (mathematics)Display devicecontent-aware image resizing retargeting liquid web layouts servlet visual saliency webdesignComputer graphics (images)Content (measure theory)RetargetingWeb pageResizingbusinessVisual saliency
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Automatic aesthetic photo composition

2013

A proper aesthetic composition of photographic content does result in an actual emotional response from the watcher. In this work we propose a fully automatic computational approach to photo composi- tion. This method takes into account well-known and widely adopted aesthetic guidelines relative to picture content as a mean for guiding an optimization framework. The resulting composition is produced as the optimal combination of cropping and retargeting. The effectiveness of the results achieved by the method are tested and evaluated with several of experiments.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryRetargetingFully automaticphoto composition retargeting visual saliencyOptimal combinationComputer visionArtificial intelligencebusinessCroppingComposition (language)Visual saliency
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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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Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

2017

Visual Saliency aims to detect the most important regions of an image from a perceptual point of view. More in detail, the goal of Visual Saliency is to build a Saliency Map revealing the salient subset of a given image by analyzing bottom-up and top-down factors of Visual Attention. In this paper we proposed a new method for Saliency detection based on colour and scale analysis, extending our previous work based on SIFT spatial density inspection. We conducted several experiments to study the relationships between saliency methods and the object attention processes and we collected experimental data by tracking the eye movements of thirty viewers in the first three seconds of observation o…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industrymedia_common.quotation_subject05 social sciencesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONEye movementExperimental dataScale-invariant feature transformVisual saliency Object-based attention SIFT Fixation maps Dataset Eye trackingPattern recognition02 engineering and technology050105 experimental psychologySalientPerceptionFixation (visual)0202 electrical engineering electronic engineering information engineeringEye tracking020201 artificial intelligence & image processing0501 psychology and cognitive sciencesComputer visionArtificial intelligencebusinessObject-based attentionmedia_common
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