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Titlebook: Computer Analysis of Images and Patterns; 15th International C Richard Wilson,Edwin Hancock,William Smith Conference proceedings 2013 Sprin

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Weighted Semi-Global Matching and Center-Symmetric Census Transform for Robust Driver Assistance,ls can be easily integrated by weighing the paths according to the gradient of the disparity. The different approaches are evaluated on the KITTI benchmark, which provides real imagery with LIDAR ground truth. The results indicate improved performance compared to state-of-the-art SGM based algorithms.
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Focus Fusion with Anisotropic Depth Map Smoothing,s a robustified data fidelity term with an anisotropic diffusion strategy that involves a matrix-valued diffusion tensor. Experiments with synthetic and real-world data show that this depth map regularisation can improve existing fusion methods substantially. Our methodology is general and can be applied to improve many existing fusion methods.
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3D Mesh Decomposition Using Protrusion and Boundary Part Detection,dvantage over the similar approach proposed by Wu and Levine [1]; our approach can find boundaries for some joining parts not entirely located in the concave region which is not the case in the work of Wu and Levine. The experimental result on the McGill and SHREC 2007 datasets show promising results for partial matching in 3D model retrieval.
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Region Based Contour Detection by Dynamic Programming,odel testing functions, in particular by means of techniques from robust statistics. The proposed framework was tested on synthetic data and real microscopic images. A performance comparison with the standard gradient-based DP and a recent non-gradient DP-based contour detection algorithm clearly demonstrates the superiority of our approach.
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0302-9743 cessing, image-based modeling, kernel methods, medical imaging, mobile multimedia, model-based vision approaches, motion analysis, natural computation for digital imagery, segmentation and grouping, and shape representation and analysis.978-3-642-40245-6978-3-642-40246-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/BFb0080541ent of depth data more practical. Quantitative experiments run on the Middlebury dataset show that our method outperforms state-of-the-art techniques in terms of accuracy and robustness to the number of frames and to the noise level.
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