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%INORM Image normalization % % g = inorm(image) % % Return a normalized image in which all pixels lie in the range % 0 to 1. % % % Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab f

% optimization target function used by camcalt % Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab function e = eightb(z, params, xw, yw, zw, X, Y) % % unpack the unknowns % f =

%INORM Image normalization % % g = inorm(image) % % Return a normalized image in which all pixels lie in the range % 0 to 1. % % % Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab f

% optimization target function used by camcalt % Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab function e = eightb(z, params, xw, yw, zw, X, Y) % % unpack the unknowns % f =

%INORM Image normalization % % g = inorm(image) % % Return a normalized image in which all pixels lie in the range % 0 to 1. % % % Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab f

% optimization target function used by camcalt % Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab function e = eightb(z, params, xw, yw, zw, X, Y) % % unpack the unknowns % f =

% Algorithm 8.1. also 11.7 % Rank based factorization algorithm for multiview reconstruction % using point features % as described in Chapter 8, "An introduction to 3-D Vision" % by Y. Ma, S. S

/* * 1394-Based Digital Camera Control Library * Allied Vision Technologies (AVT) specific extensions * Copyright (C) 2005 Inria Sophia-Antipolis * * Written by Pierre MOOS

/* * 1394-Based Digital Camera Control Library * Allied Vision Technologies (AVT) specific extensions * Copyright (C) 2005 Inria Sophia-Antipolis * * Written by Pierre MOOS

/* This program detects image features using SIFT keypoints. For more info, refer to: Lowe, D. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60,