Search results for "feature"

showing 10 items of 4091 documents

Automated Characterization of Mouth Activity for Stress and Anxiety Assessment

2016

International audience; Non-verbal information portrayed by human facial expression, apart from emotional cues also encompasses information relevant to psychophysical status. Mouth activities in particular have been found to correlate with signs of several conditions; depressed people smile less, while those in fatigue yawn more. In this paper, we present a semi-automated, robust and efficient algorithm for extracting mouth activity from video recordings based on Eigen-features and template-matching. The algorithm was evaluated for mouth openings and mouth deformations, on a minimum specification dataset of 640x480 resolution and 15 fps. The extracted features were the signals of mouth expa…

[ INFO ] Computer Science [cs]Computer scienceSpeech recognitionFeature extractionautomatic assessmentComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologymouth gesture recognition[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Yawn[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Correlation03 medical and health sciencesstress0302 clinical medicineRobustness (computer science)Stress (linguistics)[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringmedicine[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Facial expression[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]anxietyimage processingRecognition[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][SPI.OPTI]Engineering Sciences [physics]/Optics / PhotonicAnxiety020201 artificial intelligence & image processing[ SPI.OPTI ] Engineering Sciences [physics]/Optics / Photonicmedicine.symptom030217 neurology & neurosurgery
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Discrimination of coral reflectance spectra in the Red Sea

2002

Benthic populations can potentially be mapped from remotely acquired spectral imagery, provided that they have distinctive reflectance signatures. We examined the spectral reflectance characteristics of 14 genera of Red Sea coral using a submersible spectroradiometer. Coral spectra varied quantitatively and qualitatively over the depth interval 5–20 m. Tissue pigment content had a larger effect on reflectance than colony morphology. Ten coral genera could be discriminated with a statistical probability of 52% on the basis of their absolute reflectance. Six groups of two to three coral genera could be discriminated with a probability of 60% on the basis of their rates of change in reflectanc…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciences[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCoral0211 other engineering and technologies02 engineering and technologyAquatic Science01 natural sciencesSpectral line[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing14. Life underwaterComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographygeography.geographical_feature_categoryfungiPigment compositionCoral reefReflectivityWavelengthSpectroradiometerBenthic zone[SDE]Environmental SciencesEnvironmental science[SDE.BE]Environmental Sciences/Biodiversity and Ecology
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Region-based segmentation on depth images from a 3D reference surface for tree species recognition.

2013

International audience; The aim of the work presented in this paper is to develop a method for the automatic identification of tree species using Terrestrial Light Detection and Ranging (T-LiDAR) data. The approach that we propose analyses depth images built from 3D point clouds corresponding to a 30 cm segment of the tree trunk in order to extract characteristic shape features used for classifying the different tree species using the Random Forest classifier. We will present the method used to transform the 3D point cloud to a depth image and the region based segmentation method used to segment the depth images before shape features are computed on the segmented images. Our approach has be…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingFeature extractionPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Minimum spanning tree-based segmentation[STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringSegmentationComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[STAT.AP]Statistics [stat]/Applications [stat.AP]Contextual image classificationbusiness.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentation15. Life on landdepth image segmentationRandom forestdepth images from 3D point cloudsIEEE[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingsingle tree species recognitionArtificial intelligenceRange segmentationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingForest inventory
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Image registration for quality assessment of projection displays

2014

International audience; In the full reference metric based image quality assessment of projection displays, it is critical to achieve accurate and fully automatic image registration between the captured projection and its reference image in order to establish a subpixel level mapping. The preservation of geometrical order as well as the intensity and chromaticity relationships between two consecutive pixels must be maximized. The existing camera based image registration methods do not meet this requirement well. In this paper, we propose a markerless and view independent method to use an un-calibrated camera to perform the task. The proposed method including three main components: feature e…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingImage qualitybusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationKanade–Lucas–Tomasi feature trackerImage processingImage texture[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer visionArtificial intelligenceProjection (set theory)businessImage restorationMathematicsFeature detection (computer vision)
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An optimized algorithm of image stitching in the case of a multi-modal probe for monitoring the evolution of scars

2013

International audience; We propose a new system that makes possible to monitor the evolution of scars after the excision of a tumorous dermatosis. The hardware part of this system is composed of a new optical innovative probe with which two types of images can be acquired simultaneously: an anatomic image acquired under a white light and a functional one based on autofluorescence from the protoporphyrin within the cancer cells. For technical reasons related to the maximum size of the area covered by the probe, acquired images are too small to cover the whole scar. That is why a sequence of overlapping images is taken in order to cover the required area. The main goal of this paper is to des…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)Panorama[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transform[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyautofluorescence010501 environmental sciences01 natural sciencesImage stitching[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingstitchingmulti-modal probe0202 electrical engineering electronic engineering information engineeringComputer visionProjection (set theory)[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing0105 earth and related environmental sciencesbusiness.industryFluorescenceScars evolutionmonitoringAutofluorescenceTransformation (function)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmSPIE Proceedings
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A new minimum trees-based approach for shape matching with improved time computing : application to graphical symbols recognition

2010

Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longe…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMinimum spanning tree[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingActive shape model0202 electrical engineering electronic engineering information engineeringDiscrete cosine transformComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingSpanning treebusiness.industry020206 networking & telecommunicationsPattern recognitionGraphShortest path problemGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImage compression
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Sketch of an automatic image based pollen detection system

2012

The ability of measuring accurately airborne pollen concentration in the environment is an important goal for palynology. It has been unsatisfactory for agile usage to date. Huge volumes of airborne particles prevent palynologists from opportunely processing statistically suitable information. Additionally, measurements from stationary pollen monitors cannot be accurately associated to individuals. In the context of computer vision, this paper presents the outline for the structure of an image based pollen detection system, under the framework of the Personalized Pollen Profiling and Geospatial Mapping project based on individual information of allergic patient profile measured at multiple …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage ProcessingPollen Recognition[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingClassification[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingFeature Extraction[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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A classification approach to prostate cancer localization in 3T Multi-Parametric MRI

2016

International audience; Multiparametric-magnetic resonance imaging (mp-MRI) has demonstrated, in many studies, its potential in prostate cancer detection and analysis. We propose a supervised classification approach based on mp-MRI data base of 20 patients, in order to localize prostate cancer and to achieve a cartographic representation of the prostate voxels based on classification results. Proposed method provides a computer aided detection (CAD) software for prostatic cancer. For that, we have extracted varied features providing functional, anatomical and metabolic information helping the classifier to distinguish between three different classes ("Healthy", "Benign" and "Pathologic"). W…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[SPI] Engineering Sciences [physics][INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceSVMFeature extractionWord error ratecomputer.software_genre030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer[SPI]Engineering Sciences [physics]0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingProstateVoxelmedicine[ SPI ] Engineering Sciences [physics]Computer visionProstate cancermedicine.diagnostic_testbusiness.industryPattern recognitionMagnetic resonance imagingSpectramedicine.disease3. Good healthRandom forestSupport vector machinemedicine.anatomical_structuremp-MRIArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryRandom forest
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Distribution and ecology of the Globigerinoides ruber — Globigerinoides elongatus morphotypes in the Azores region during the late Pleistocene-Holoce…

2018

Abstract Globigerinoides ruber is the dominant taxon in the North Atlantic Subtropical Gyre, nowadays limited to the north by the Azores Current. It is highly sensitive to recent and late Pleistocene Azores Front Current System variability. In this study, we analyse the distribution of five individual morphotypes of the G. ruber – G. elongatus plexus (G. ruber s.s., G. ruber cyclostoma type, G. elongatus, G. elongatus cf.1, G. elongatus pyramidical type) and G. ruber kummerform gr. in a core (ATA13-OF-KT1) collected southwest of the Azores islands and located in a strategical position near the present-day boundary of the Subtropical Gyre/Azores Front Current System (STG/AFCS). Micropaleonto…

[ SDU.OCEAN ] Sciences of the Universe [physics]/Ocean AtmospherePlanktonic foraminifera010506 paleontology010504 meteorology & atmospheric sciencesPleistoceneCyclostomaOceanography01 natural sciencesPaleontologyPaleoceanographyOcean gyre[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environment14. Life underwaterGlacial periodPaleoclimatology[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentRelative species abundanceEcology Evolution Behavior and SystematicsHoloceneGlobigerinoidesComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesEarth-Surface Processes[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmospheregeographygeography.geographical_feature_categorybiologyEcologyAzores front/current systemPaleontology15. Life on landbiology.organism_classificationStable isotopeEcology Evolution Behavior and SystematicOceanographyEarth-Surface ProcesseInterglacialSubtropical gyreGeology
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Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO

2016

This paper presents an improved wave kernel signature (WKS) using the modified particle swarm optimization (MPSO)-based intelligent recognition and matching on 3D shapes. We select the first feature vector from WKS, which represents the 3D shape over the first energy scale. The choice of this vector is to reinforce robustness against non-rigid 3D shapes. Furthermore, an optimized WKS-based method for extracting key-points from objects is introduced. Due to its discriminative power, the associated optimized WKS values with each point remain extremely stable, which allows for efficient salient features extraction. To assert our method regarding its robustness against topological deformations,…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO ] Computer Science [cs]Matching (graph theory)Feature vectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[INFO] Computer Science [cs][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Kernel (linear algebra)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Discriminative modelRobustness (computer science)0202 electrical engineering electronic engineering information engineeringFeature (machine learning)[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSMathematicsbusiness.industryParticle swarm optimization[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognition020201 artificial intelligence & image processingArtificial intelligencebusinessEnergy (signal processing)
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