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The Inverse Compositional Algorithm for Parametric Motion Estimation -------------------------------------------------------------------- ******* SUMMARY ******* This program implements the inverse compositional algorithm for parametric motion estimation. It computes a planar transformation between two images, including translations, similarities, affinities and homographies. It computes large displacements through a pyramidal scheme and uses robust functionals to deal with noise and occlusions. Reference articles: [1] S. Baker and I. Matthews, Lucas-kanade 20 years on: A unifying framework, International journal of computer vision, 56 (2004), pp. 221-255. [2] S. Baker, R. Gross, I. Matthews, and T. Ishikawa, Lucas-kanade 20 years on: A unifying framework: Part 2, Tech. Report CMU-RI-TR-03-01, Robotics Institute, Pittsburgh, PA, February 2003. This program is part of an IPOL publication: http://www.ipol.im/ ****** AUTHOR ****** Javier Sánchez Pérez <jsanchez@dis.ulpgc.es> Centro de Tecnologías de la Imagen (CTIM) Universidad de Las Palmas de Gran Canaria ******* VERSION ******* Version 1, released on October 9, 2015 ******* LICENSE ******* This program is free software: you can use, modify and/or redistribute it under the terms of the simplified BSD License. You should have received a copy of this license along this program. If not, see <http://www.opensource.org/licenses/bsd-license.html>. Copyright (C) 2015, Javier Sánchez Pérez <jsanchez@dis.ulpgc.es> All rights reserved. *********** COMPILATION *********** Required environment: Any unix-like system with a standard compilation environment (make and C and C++ compilers) Required libraries: libpng, lipjpeg, libtiff Compilation instructions: run "make" to produce an executable "inverse_compositional_algorithm" ***** USAGE ***** The program reads two input images, take some parameters and produce a parametric model. The meaning of the parameters is thoroughly discussed on the accompanying IPOL article. Usage instructions: <Usage>: inverse_compositional_algorithm image1 image2 [OPTIONS] OPTIONS: -------- -f name Name of the output filename that will contain the computed transformation -n N Number of scales for the coarse-to-fine scheme -z F Zoom factor used in the coarse-to-fine scheme Values must be in the range (0,1) -e F Threshold for the convergence criterion -t N Transformation type to be computed: 2-traslation; 3-Euclidean transform; 4-similarity 6-affinity; 8-homography -r N Use robust error functions: 0-Non robust (L2 norm); 1-truncated quadratic 2-German & McLure; 3-Lorentzian 4-Charbonnier -l F Value of the parameter for the robust error function A value <=0 if it is automatically computed -v Switch on verbose mode. Execution examples: 1.Default parameters: >inverse_compositional_algorithm input/homography1.png input/homography2.png 2.Computing an affinity with the truncated quadratic and verbose mode: >inverse_compositional_algorithm input/homography1.png input/homography2.png -t 6 -r 1 -v If a parameter is given an invalid value it will take a default value. ************* LIST OF FILES ************* bicubic_interpolation.cpp: Computes the bicubic interpolation of an image file.cpp: Functions for input/output iio.c: Functions to read and write images inverse_compositional_algorithm.cpp: Implementation of the method main.cpp: Main algorithm to read the command line parameters mask.cpp: Function to compute the gradient of an image and apply a Gaussian matrix.cpp: Multiplication of matrices and vectors and calculating the inverse transformation.cpp: Compute the Jacobian and the composition of transformations zoom.cpp: Compute the zoom-out of an image and the zoom-in of the parameters Complementary programs (used for the online demo only): output.cpp: Program to compute some images and error metrics from the results noise.cpp: Program to add Gaussian noise to the input images mt19937ar.c: Program to generate random numbers, used in noise.cpp
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