Search results for "Feature descriptor"

showing 5 items of 5 documents

Global Archaelogical Mosaicing for Underwater Scenes

2006

This contribution regards the mosaicing of seabed landscapes, in order to represent higher resolution photos of whole sites with wrecks in a fast and safe fashion. A stereo vision system has been arranged by adding two cameras to the payload aboard a Remotely Operated Vehicle. A number of problems arise due to poor luminosity, cloudy water, water distortion and presence of artifacts. A robust algorithm has been defined to reduce the radial distortion of the camera lenses and to enhance the results.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticamosaicing feature detectors feature descriptors
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New Error Measures to Evaluate Features on Three-Dimensional Scenes

2011

In this paper new error measures to evaluate image features in three-dimensional scenes are proposed and reviewed. The proposed error measures are designed to take into account feature shapes, and ground truth data can be easily estimated. As other approaches, they are not error-free and a quantitative evaluation is given according to the number of wrong matches and mismatches in order to assess their validity

Ground truthFeature Detector Feature Descriptor Overlap Error Epipolar Geometry Feature Matching and ComparisonSettore INF/01 - InformaticaFeature (computer vision)business.industryEpipolar geometryFeature descriptorPattern recognitionArtificial intelligencebusinessFeature matchingMathematics
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Underwater archaeological mosaicing

2006

Archaeological mosaicing is one of the challenges of the computer vision community and it can be faced in a 2D or 3D approach. This contribution regards a methodology to do a mosaic of an underwater bi-dimensional scene. A number of problems arise from the acquisition of images by a remote operated vehicle. Radial distortion, poor luminosity, cloud water, presence of artefacts are part of the issues that can occur; for instance, the radial distortion has been corrected to improve the quality of the input images. Keypoints detection (through SIFT transform), Singular Value Decomposition, Random Samples Consensus are some of the techniques applied in our method. This contribution regards the …

mosaicing feature descriptor feature detector
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Multimodal Images Classification using Dense SURF, Spectral Information and Support Vector Machine

2019

International audience; The multimodal image classification is a challenging area of image processing which can be used to examine the wall painting in the cultural heritage domain. In such classification, a common space of representation is important. In this paper, we present a new method for multimodal representation learning, by using a pixel-wise feature descriptor named dense Speed Up Robust Features (SURF) combined with the spectral information carried by the pixel. For classification of extracted features we have used support vector machine (SVM). Our database was extracted from acquisition on cultural heritage wall paintings that contain four modalities UV, Visible, IRR and fluores…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyImage (mathematics)0202 electrical engineering electronic engineering information engineeringFeature descriptorRepresentation (mathematics)Spectral informationSpeeded up robust features SURFGeneral Environmental SciencePixelbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsPattern recognitionSVM classificationSupport vector machineCultural heritageMultimodal imagesCielab spaceDense features[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]General Earth and Planetary Sciences020201 artificial intelligence & image processingArtificial intelligencebusinessFeature learning
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Extraction and fusion of spectral parameters for face recognition

2011

This is the copy of journal's version originally published in Proc. SPIE 7877: http://spie.org/x10.xml?WT.svl=tn7. Reprinted with permission of SPIE. Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately …

Near Infrared[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingBiometrics[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingInfraredComputer scienceElectromagnetic spectrumFeature extractionImage processing02 engineering and technologyShort Wave Infrared[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingGrayscaleFacial recognition system[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringFeature descriptorComputer visionFace recognition[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryNear-infrared spectroscopyVisibleFeature extraction020201 artificial intelligence & image processingArtificial intelligencefeature descriptorbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]
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