00001 /*!@file Surprise/SingleChannelSurprise.H Channel for a single stream of processing. */ 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: Laurent Itti <itti@usc.edu> 00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/Surprise/SingleChannelSurprise.H $ 00035 // $Id: SingleChannelSurprise.H 10107 2008-08-15 06:45:49Z mundhenk $ 00036 // 00037 00038 #ifndef SINGLECHANNELSURPRISE_H_DEFINED 00039 #define SINGLECHANNELSURPRISE_H_DEFINED 00040 00041 #include "Channels/SubmapAlgorithm.H" 00042 #include "Component/ModelParam.H" 00043 #include "Image/LevelSpec.H" 00044 #include "Surprise/SurpriseMap.H" 00045 #include <vector> 00046 00047 // ###################################################################### 00048 //! SingleChannelSurprise is a Surprise extension to SingleChannel 00049 /*! This class only provides the computation of surprise. Typically 00050 you would first build a SingleChannel (or derivative), then build 00051 a SingleChannelSurprise, then pass the SingleChannelSurprise to 00052 the channel's setSubmapAlgorithm(). See VisualCortexSurprise for 00053 example usage. */ 00054 template <class SMODEL> 00055 class SingleChannelSurprise : public SubmapAlgorithm 00056 { 00057 public: 00058 //! Constructor 00059 SingleChannelSurprise(OptionManager& mgr); 00060 00061 //! destructor 00062 virtual ~SingleChannelSurprise(); 00063 00064 //! get a surprise map 00065 /*! Pass a submap index and a submap, and you'll get back the 00066 associated surprise */ 00067 Image<float> getSurpriseMap(const uint index, 00068 const Image<float>& submap); 00069 00070 //! Compute the i'th submap for the given channel 00071 virtual Image<float> compute(const SingleChannel& chan, const uint i); 00072 00073 protected: 00074 OModelParam<uint> itsSQlen; //!< number of surprise maps 00075 OModelParam<double> itsUpdateFac; //!< update factor 00076 OModelParam<double> itsNeighUpdateFac; //!< update factor for neighbors 00077 NModelParam<double> itsInitialVal; //!< Initial values 00078 NModelParam<double> itsInitialVar; //!< Initial variance 00079 NModelParam<double> itsBgVal; //!< Background values 00080 OModelParam<float> itsNeighSigma; //!< Neighborhood sigma 00081 OModelParam<float> itsLocSigma; //!< Local neighborhood sigma 00082 OModelParam<bool> itsTakeSTMax; //!< Use Max for space-time 00083 OModelParam<bool> itsLogged; //!< Do we dump data to a log file 00084 OModelParam<LevelSpec> itsLevelSpec; //!< our levelspec 00085 OModelParam<Point2D<int> > itsProbe; //!< location of a virtusl electrode 00086 OModelParam<double> itsSLfac; //!< fact for local temporal surprise 00087 OModelParam<double> itsSSfac; //!< factor for spatial surprise 00088 OModelParam<std::string> itsJointKLBiasTypeStr; 00089 00090 // get us started (see ModelComponent.H) 00091 virtual void start1(); 00092 00093 private: 00094 SingleChannelSurprise(const SingleChannelSurprise&); // not allowed 00095 SingleChannelSurprise& operator=(const SingleChannelSurprise&); // not allow 00096 std::vector< SurpriseMap<SMODEL> > itsSmap; 00097 00098 //! log entry number 00099 uint itsLogEntry; 00100 SU_KL_BIAS itsJointKLBiasType; 00101 }; 00102 00103 #endif 00104 00105 /* So things look consistent in everyone's emacs... */ 00106 /* Local Variables: */ 00107 /* indent-tabs-mode: nil */ 00108 /* End: */
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