00001 /*!@file SIFT/SIFThough.H Data structure for SIFT Hough transform */ 00002 00003 // //////////////////////////////////////////////////////////////////// // 00004 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2001 by the // 00005 // University of Southern California (USC) and the iLab at USC. // 00006 // See http://iLab.usc.edu for information about this project. // 00007 // //////////////////////////////////////////////////////////////////// // 00008 // Major portions of the iLab Neuromorphic Vision Toolkit are protected // 00009 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency // 00010 // in Visual Environments, and Applications'' by Christof Koch and // 00011 // Laurent Itti, California Institute of Technology, 2001 (patent // 00012 // pending; application number 09/912,225 filed July 23, 2001; see // 00013 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status). // 00014 // //////////////////////////////////////////////////////////////////// // 00015 // This file is part of the iLab Neuromorphic Vision C++ Toolkit. // 00016 // // 00017 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can // 00018 // redistribute it and/or modify it under the terms of the GNU General // 00019 // Public License as published by the Free Software Foundation; either // 00020 // version 2 of the License, or (at your option) any later version. // 00021 // // 00022 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope // 00023 // that it will be useful, but WITHOUT ANY WARRANTY; without even the // 00024 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR // 00025 // PURPOSE. See the GNU General Public License for more details. // 00026 // // 00027 // You should have received a copy of the GNU General Public License // 00028 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write // 00029 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, // 00030 // Boston, MA 02111-1307 USA. // 00031 // //////////////////////////////////////////////////////////////////// // 00032 // 00033 // Primary maintainer for this file: James Bonaiuto <bonaiuto@usc.edu> 00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/SIFT/SIFThough.H $ 00035 // $Id: SIFThough.H 4938 2005-07-14 20:44:30Z rjpeters $ 00036 // 00037 00038 #ifndef SIFTHOUGH_H_DEFINED 00039 #define SIFTHOUGH_H_DEFINED 00040 00041 #include <vector> 00042 00043 //! SIFThough accumalates data for the Hough transform used in SIFT 00044 /*! This class is used to accumulate evidence for various possible 00045 geometric transforms which are compatible with pairs of matching 00046 keypoints. Here we do not solve the general affine transform 00047 problem, rather we rely on simple differences between the data 00048 available in Keypoint, namely: x, y, scale, and orientation. We tile 00049 each dimension into eight bins, yielding a total of 4096 bins. Each 00050 pair of matching keypoints votes for 16 bins with linear 00051 interpolation (i.e., for two adjacent bins in each dimension. The 00052 philosophy and implementation here is very similar to that of 00053 FeatureVector. */ 00054 class SIFThough 00055 { 00056 public : 00057 //! Constructor 00058 SIFThough(); 00059 00060 //! Destructor 00061 ~SIFThough(); 00062 00063 //! add value 00064 /*! Linearly add a value. Indices are as follows: 00065 0.0 <= dx <= 8.0 : [0 .. 7] dx=2.0 falls equally between bins 1 and 2; 00066 0.0 <= dy <= 8.0 : [0 .. 7] dy=2.0 falls equally between bins 1 and 2; 00067 0.0 <= do <= 8.0 : [0 .. 7] do=4.0 falls equally between bins 3 and 4; 00068 0.0 <= ds <= 8.0 : [0 .. 7] ds=4.0 falls equally between bins 3 and 4; 00069 Note that the orientation dimension is different as it has Dirichlet 00070 boundary conditions. */ 00071 void addValue(const float dx, const float dy, const float doo, 00072 const float ds, const float value); 00073 00074 //! Get the parameter values at the peak 00075 void getPeak(float& dx, float& dy, float& doo, float& ds) const; 00076 00077 private: 00078 std::vector<float> itsData; // vector of data 00079 }; 00080 00081 00082 // ###################################################################### 00083 // Inlined member functions 00084 // ###################################################################### 00085 00086 00087 00088 #endif 00089 00090 // ###################################################################### 00091 /* So things look consistent in everyone's emacs... */ 00092 /* Local Variables: */ 00093 /* indent-tabs-mode: nil */ 00094 /* End: */
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