0000000000461635

AUTHOR

Anastasia Zakharova

showing 4 related works from this author

Entire Reflective Object Surface Structure Understanding

2015

International audience

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer sciencebusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSurface structureComputer visionArtificial intelligenceObject (computer science)businessComputingMilieux_MISCELLANEOUS
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Entire reflective object surface structure understanding based on reflection motion estimation

2015

An sub-segmentation method for the reflective surface structure understanding.The use of reflection motion features as spatiotemporal coherence for video segmentation.Straightforward implementation.A building block for object recognition. The presence of reflection on a surface has been a long-standing problem for object recognition since it brings negative effects on object's color, texture and structural information. Because of that, it is not a trivial task to recognize the surface structure affected by the reflection, especially when the object is entirely reflective. Most of the cases, reflection is considered as noise. In this paper, we propose a novel method for entire reflective obj…

Surface (mathematics)business.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCognitive neuroscience of visual object recognitionObject (computer science)Artificial IntelligenceMotion estimationSignal ProcessingComputer visionComputer Vision and Pattern RecognitionNoise (video)Specular reflectionArtificial intelligenceReflection (computer graphics)businessSoftwareComputingMethodologies_COMPUTERGRAPHICSCoherence (physics)MathematicsPattern Recognition Letters
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Manufactured object sub-segmentation based on reflection motion estimation

2015

International audience; In computer vision, reflection is a long-standing problem, it covers image textures, makes original color difficult to recognize, complicates the understanding of the scene. Most of the time, it is considered as “noise”. Many methods are proposed in order to reduce or delete the reflection effects in the image, but generally, the performances are not quite satisfactory. While instead of working on “de-noising”, we propose a method to take advantage of moving reflections that can be used for different computer vision applications. For instance, the segmentation of reflective manufactured objects is presented in this paper. We focus on tracking reflection components an…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognition02 engineering and technologyImage segmentation01 natural sciencesScale space010309 opticsImage texture[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion growingMotion estimation0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceReflection (computer graphics)businessMathematics
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Depth reconstruction by means of defocused light from incomplete measurements

2013

National audience

[SPI.OPTI] Engineering Sciences [physics]/Optics / Photonic[SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic[ SPI.OPTI ] Engineering Sciences [physics]/Optics / PhotonicComputingMilieux_MISCELLANEOUS
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