This a research (and didactic) oriented toolbox to explore the PROSAC algorithm. The functions are reasonably well documented and there is a directory containing examples to estimate lines and homographies in presence of outliers. However a previous exposure to the algorithm may be very helpful in understanding the options available. I am currently trying to finish a tutorial, a sort of RANSAC for dummies, but it is still work in progress: keep an eye on my web page

ST_pub
......\arrow3D.m
......\circle.pgm
......\circuit.tif
......\ColorSpec_LongName_to_RGBvalue.m
......\ColorSpec_ShortName_to_RGBvalue.m
......\difference_of_gaussian_kernels.m
......\eigen_decomposition.m
......\html
......\....\structureTensorDemo.html





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......\oneColor.pgm
......\partial_derivative_3D.m
......\partial_derivative_to_structure_tensor_form.m
......\rampStep.pgm
......\rotatePoints.m
......\stepEdge.pgm
......\structureTensorDemo.m
......\structure_tensor_plot.m
......\test_image.m
......\three_dimensional_test_cases.m
......\visualize_3D_cases_of_structure_tensor_in_ellipse_form.m
......\visualize_3D_data.m
......\voxel_plot.m

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