Search results for "Histograms"

showing 3 items of 3 documents

Improving point matching on multimodal images using distance and orientation automatic filtering

2016

International audience; Speed Up Robust Features SURF is one of the most popular and efficient methods used for image registration task. In order to achieve a correct registration, a good matching of feature point is required. However in the case of multimodal images, the high and non-linear intensity changes between different modalities led to many outliers (mismatching of detected points) and consequently a fail in the registration. Therefore, in this paper we introduce an efficient method devoted to the detection and removal of such outlier. It's based on an automatic filtering of outliers on both distance and orientation between features points. We tested our proposed method on a set of…

HistogramsComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registration02 engineering and technologyimage matchingfeature point matchingRANSACElectronic mailautomatic outlier filteringHistogramautomatic orientation filteringhigh-nonlinear intensity[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringautomatic distance filteringOutlier detectionComputer visionIR visible imagesRobustnessmultimodal imagesUV imagesImage registrationimage filteringMeasurementbusiness.industryFeature matchingSURF020206 networking & telecommunicationsPoint set registrationPattern recognitionDetectorsdetected point mismatchingcultural heritagefluorescence imagesElectronic mail[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Outlierspeed-up robust featuresFeature extraction020201 artificial intelligence & image processingAnomaly detectionArtificial intelligencebusiness
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Learning Bag of Spatio-Temporal Features for Human Interaction Recognition

2019

Bag of Visual Words Model (BoVW) has achieved impressive performance on human activity recognition. However, it is extremely difficult to capture high-level semantic meanings behind video features with this method as the spatiotemporal distribution of visual words is ignored, preventing localization of the interactions within a video. In this paper, we propose a supervised learning framework that automatically recognizes high-level human interaction based on a bag of spatiotemporal visual features. At first, a representative baseline keyframe that captures the major body parts of the interacting persons is selected and the bounding boxes containing persons are extracted to parse the poses o…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Sum of HistogramsBag of Visual WordsHuman interaction[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSVMEdge-based regionMSER3D-SIFT
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Time Unification on Local Binary Patterns Three Orthogonal Planes for Facial Expression Recognition

2019

International audience; Machine learning has known a tremendous growth within the last years, and lately, thanks to that, some computer vision algorithms started to access what is difficult or even impossible to perceive by the human eye. While deep learning based computer vision algorithms have made themselves more and more present in the recent years, more classical feature extraction methods, such as the ones based on Local Binary Patterns (LBP), still present a non negligible interest, especially when dealing with small datasets. Furthermore, this operator has proven to be quite useful for facial emotions and human gestures recognition in general. Micro-Expression (ME) classification is…

human eyeHistogramsgeometryUnificationComputer scienceLocal binary patternsoptimisationFeature extraction02 engineering and technologyhuman gestures recognitionFacial recognition systemcomputer visionVideos[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]time unification method03 medical and health sciences0302 clinical medicineMathematical modelLBPemotion recognition0202 electrical engineering electronic engineering information engineeringfacial emotionsfacial expression recognitionlocal binary patternsFace recognitionContextual image classificationArtificial neural networkbusiness.industryDeep learningdeep learning[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionComputational modelingmicroexpression classificationInterpolationorthogonal planesneural netsmachine learning[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Micro expressionFeature extraction020201 artificial intelligence & image processinglearning (artificial intelligence)Artificial intelligencebusiness030217 neurology & neurosurgeryGestureimage classification
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