0000000000283036

AUTHOR

Mohammed Rziza

0000-0003-4974-5903

showing 3 related works from this author

Efficient Dense Disparity Map Reconstruction using Sparse Measurements

2018

International audience; In this paper, we propose a new stereo matching algorithm able to reconstruct efficiently a dense disparity maps from few sparse disparity measurements. The algorithm is initialized by sampling the reference image using the Simple Linear Iterative Clustering (SLIC) superpixel method. Then, a sparse disparity map is generated only for the obtained boundary pixels. The reconstruction of the entire disparity map is obtained through the scanline propagation method. Outliers were effectively removed using an adaptive vertical median filter. Experimental results were conducted on the standard and the new Middlebury datasets show that the proposed method produces high-quali…

Vertical Median FilterPixelbusiness.industryComputer scienceScanline PropagationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONStereo matchingBoundary (topology)[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognition[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Scan lineStereo Matching[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Sampling (signal processing)Computer Science::Computer Vision and Pattern RecognitionOutlierMedian filterArtificial intelligenceSuperpixelCluster analysisbusiness
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ACCURATE DENSE STEREO MATCHING FOR ROAD SCENES

2017

International audience; Stereo matching task is the core of applications linked to the intelligent vehicles. In this paper, we present a new variant function of the Census Transform (CT) which is more robust against radiometric changes in real road scenes. We demonstrate that the proposed cost function outperforms the conventional cost functions using the KITTI benchmark. The cost aggregation method is also updated for taking into account the edge information. This enables to improve significantly the aggregated costs especially within homogenous regions. The Winner-Takes-All (WTA) strategy is used to compute disparity values. To further eliminate the remainder matching ambiguities , a post…

Computer sciencebusiness.industry[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO][INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]0211 other engineering and technologiesStereo matchingCross Comparison Census02 engineering and technologyStereo visionCross based aggregationStereopsisCensus TransformRobustness (computer science)0202 electrical engineering electronic engineering information engineeringRadiometry[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness021101 geological & geomatics engineering
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Optical flow estimation from multichannel spherical image decomposition

2011

The problem of optical flow estimation is largely discussed in computer vision domain for perspective images. It was also proven that, in terms of optical flow analysis from these images, we have difficulty distinguishing between some motion fields obtained with little camera motion. The omnidirectional cameras provided images with large filed of view. These images contain global information about motion and allow to remove the ambiguity present in perspective case. Nevertheless, these images contain significant radial distortions that is necessary to take into account when treating these images to estimate the motion. In this paper, we shall describe new way to compute efficient optical fl…

business.industryPerspective (graphical)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowPhysics::OpticsMotion (geometry)Spherical imageImage (mathematics)WaveletComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligenceDecomposition method (constraint satisfaction)businessOmnidirectional antennaSoftwareMathematicsComputer Vision and Image Understanding
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