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dataStructures

PURPOSE ^

dataStructures - lists the data structures used in the SaliencyToolbox.

SYNOPSIS ^

This is a script file.

DESCRIPTION ^

 dataStructures - lists the data structures used in the SaliencyToolbox.

 DATA STRUCTURES USED IN THE SALIENCYTOOLBOX

 Global variables
    IS_INITIALIZED: flag that initializeGlobal was called.
    IMG_EXTENSIONS: cell arrays with possible extensions for image files.
         DEBUG_FID: file identifier for debugMsg output.
                PD: path delimiter for your operating system.
          BASE_DIR: base directory for data and image locations.
           IMG_DIR: directory for images.
          DATA_DIR: directory for data.
           TMP_DIR: directory for temporary files.

  See also initializeGlobal, declareGlobal, debugMsg.


 Image - stores information about an image.
   filename: the file name relative to IMG_DIR.
       data: the image data (UINT8 or double)
             Each image structure has to contain the filename or the data
             field. It can have both.
       type: some text label.
       size: the size of the image.
       dims: the number of dimensions of the image (2 or 3).
       date: time stamp.

 See also initializeImage.


 Map - 2d data structure with extra information.
     origImage: Image from which this map was computed.
         label: text label identying the map.
          data: 2d array with the map data.
          date: time stamp.
    parameters: parameters used for generating this map.

 See also displayMap, displayMaps.


 Pyramid - a multi-resolution pyramid for a particular feature.
    origImage: the source image.
        label: text label denoting the feature.
         type: type of subsampling, one of: 'dyadic','sqrt2','TopDown'.
       levels: vector of maps containing the levels of this pyramid.
         date: time stamp.

 See also makeFeaturePyramids, displayPyramid, runSaliency.


 SaliencyParams - set of parameters used for generating a saliency map.
               foaSize: size of the focus of attention for disk-IOR.
           pyramidType: 'dyadic' or 'sqrt2'.
              features: cell array of the features to be used for saliency computation
                        possible values: 'Color', 'Intensities', 'Orientations', 'Skin','TopDown'.
               weights: vector of weights for each feature (same length as features)
               IORtype: type of inhibition of return, one of: 'shape','disk','None'.
             shapeMode: one of: 'None','shapeSM','shapeCM','shapeFM','shapePyr'.
           levelParams: structure with pyramid level parameters.
              normtype: Map normalization type, one of: 'None','LocalMax','Iterative'.
               numIter: Number of iterations for 'Iterative' normtype.
             useRandom: Use random jitter (1) or not (0) for converting coodinates.
    segmentComputeType: Method for shape segmentation, one of: 'Fast','LTU'.
         smOutputRange: saliency map output in Amperes (1e-9).
             noiseAmpl: amplitude of random noise (1e-17).
            noiseConst: amplitude of contant noise (1e-14).
           gaborParams: structure with parameters for Gabor orientation filters.
             oriAngles: vector with orientation angles (in degrees).
    visualizationStyle: style used for visualizing attended locations,
                        one of: 'Contour', 'ContrastModulate', 'None'.

 See also diskIOR, makeGaussianPyramid, makeSaliencyMap, applyIOR, estimateShape,
          centerSurround, maxNormalize, winnerToImgCoords, makeGaborFilter,
          defaultGaborParams, defaultLevelParams, plotSalientLocation.


 levelParams - a structure with parameters for pyramid levels for
               center-surround operations
     minLevel: lowest pyramid level (starting at 1) for center-surround computations.
     maxLevel: highest pyramid level for center-surround.
     minDelta: minimum distance (levels) between center and surround.
     maxDelta: maximum distance (levels) between center and surround.
     mapLevel: pyramid level for all maps, including the saliency map.

 See also defaultLevelParams, centerSurround, winnerToImgCoords.


 gaborParams - a structure with parameters for Gabor orientation filters.
       filterPeriod: the period of the filter in pixels.
         elongation: the ratio of length versus width.
         filterSize: the size of the filter in pixels.
             stddev: the standard deviation of the Gaussian envelope in pixels.
             phases: the phase angles to be used.

 See also defaultGaborParams, makeGaborFilter, gaborFilterMap, makeOrientationPyramid.


 hueParams - describes 2d Gaussian color distribution in CIE space.
        muR: mean value in the CR direction.
       sigR: standard deviation in the CR direction.
        muG: mean value in the CG direction.
       sigG: standard deviation in the CG direction.
        rho: correlation coefficient between CR and CG.

 See also hueDistance, makeHuePyramid, skinHueParams.


 saliencyData - a vector of structures for each feature with additional
                information from computing the saliency map.
      origImage: Image structure of the input image.
          label: the feature name.
            pyr: a vector of pyramids for this feature.
             FM: a vector of feature maps.
       csLevels: the center and surround levels used to
                 compute the feature maps from the pyramids.
             CM: the conspicuity map for this feature.
           date: time stamp.

 See also makeSaliencyMap, estimateShape, runSaliency.


 shapeData - information about the shape of the attended regions.
       origImage: the Image structure for the source image.
          winner: the winning location in saliency map coordinates.
      winningMap: the map for the most salient feature at the winner location.
         iorMask: the mask used for shape-based inhibition of return.
       binaryMap: a binary map of the attended region.
    segmentedMap: the winning map segmented by the binary map.
        shapeMap: a smoothed version of segmentedMap.
            date: time stamp.

 See also estimateShape, shapeIOR, applyIOR, plotSalientLocation, runSaliency.


 WTA - a winner-take-all neural network.
       sm: LIF neuron field for input from the saliency map.
      exc: excitatory LIF neurons field.
    inhib: inhibitory inter-neuron.

 See also initializeWTA, evolveWTA.


 LIF - leaky integrate and fire neuron (field).
     timeStep: time step for integration (in sec).
        Eleak: leak potential (in V).
         Eexc: potential for excitatory channels (positive, in V).
         Einh: potential for inhibitory channels (negative, in V).
        Gleak: leak conductivity (in S).
         Gexc: conductivity of excitatory channels (in S).
         Ginh: conductivity of inhibitory channels (in S).
    GinhDecay: time constant for decay of inhibitory conductivity (in S).
       Ginput: input conductivity (in S).
      Vthresh: threshold potential for firing (in V).
            C: capacity (in F).
         time: current time (in sec).
            V: current membrane potential (in V) - can be an array for several neurons.
            I: current input current (in A) - can be an array for several neurons.
     DoesFire: neuron can (1) or cannot (0) fire.

 See also defaultLeakyIntFire, evolveLeakyIntFire, initializeWTA.


   LTUnetwork - a network of N linear threshold units.
    connections: N x N weight matrix, a sparse matrix.
     thresholds: 1 x N vector with thresholds for the units.
      input_idx: the indices of all input units in the network.
     output_idx: the indices of all output units in the network.
       numCells: the number of units.
          label: a text label fo the network.

 See also LTUsimulate, LTUsegmentMap, makeLTUsegmentNetwork.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 % dataStructures - lists the data structures used in the SaliencyToolbox.
0002 %
0003 % DATA STRUCTURES USED IN THE SALIENCYTOOLBOX
0004 %
0005 % Global variables
0006 %    IS_INITIALIZED: flag that initializeGlobal was called.
0007 %    IMG_EXTENSIONS: cell arrays with possible extensions for image files.
0008 %         DEBUG_FID: file identifier for debugMsg output.
0009 %                PD: path delimiter for your operating system.
0010 %          BASE_DIR: base directory for data and image locations.
0011 %           IMG_DIR: directory for images.
0012 %          DATA_DIR: directory for data.
0013 %           TMP_DIR: directory for temporary files.
0014 %
0015 %  See also initializeGlobal, declareGlobal, debugMsg.
0016 %
0017 %
0018 % Image - stores information about an image.
0019 %   filename: the file name relative to IMG_DIR.
0020 %       data: the image data (UINT8 or double)
0021 %             Each image structure has to contain the filename or the data
0022 %             field. It can have both.
0023 %       type: some text label.
0024 %       size: the size of the image.
0025 %       dims: the number of dimensions of the image (2 or 3).
0026 %       date: time stamp.
0027 %
0028 % See also initializeImage.
0029 %
0030 %
0031 % Map - 2d data structure with extra information.
0032 %     origImage: Image from which this map was computed.
0033 %         label: text label identying the map.
0034 %          data: 2d array with the map data.
0035 %          date: time stamp.
0036 %    parameters: parameters used for generating this map.
0037 %
0038 % See also displayMap, displayMaps.
0039 %
0040 %
0041 % Pyramid - a multi-resolution pyramid for a particular feature.
0042 %    origImage: the source image.
0043 %        label: text label denoting the feature.
0044 %         type: type of subsampling, one of: 'dyadic','sqrt2','TopDown'.
0045 %       levels: vector of maps containing the levels of this pyramid.
0046 %         date: time stamp.
0047 %
0048 % See also makeFeaturePyramids, displayPyramid, runSaliency.
0049 %
0050 %
0051 % SaliencyParams - set of parameters used for generating a saliency map.
0052 %               foaSize: size of the focus of attention for disk-IOR.
0053 %           pyramidType: 'dyadic' or 'sqrt2'.
0054 %              features: cell array of the features to be used for saliency computation
0055 %                        possible values: 'Color', 'Intensities', 'Orientations', 'Skin','TopDown'.
0056 %               weights: vector of weights for each feature (same length as features)
0057 %               IORtype: type of inhibition of return, one of: 'shape','disk','None'.
0058 %             shapeMode: one of: 'None','shapeSM','shapeCM','shapeFM','shapePyr'.
0059 %           levelParams: structure with pyramid level parameters.
0060 %              normtype: Map normalization type, one of: 'None','LocalMax','Iterative'.
0061 %               numIter: Number of iterations for 'Iterative' normtype.
0062 %             useRandom: Use random jitter (1) or not (0) for converting coodinates.
0063 %    segmentComputeType: Method for shape segmentation, one of: 'Fast','LTU'.
0064 %         smOutputRange: saliency map output in Amperes (1e-9).
0065 %             noiseAmpl: amplitude of random noise (1e-17).
0066 %            noiseConst: amplitude of contant noise (1e-14).
0067 %           gaborParams: structure with parameters for Gabor orientation filters.
0068 %             oriAngles: vector with orientation angles (in degrees).
0069 %    visualizationStyle: style used for visualizing attended locations,
0070 %                        one of: 'Contour', 'ContrastModulate', 'None'.
0071 %
0072 % See also diskIOR, makeGaussianPyramid, makeSaliencyMap, applyIOR, estimateShape,
0073 %          centerSurround, maxNormalize, winnerToImgCoords, makeGaborFilter,
0074 %          defaultGaborParams, defaultLevelParams, plotSalientLocation.
0075 %
0076 %
0077 % levelParams - a structure with parameters for pyramid levels for
0078 %               center-surround operations
0079 %     minLevel: lowest pyramid level (starting at 1) for center-surround computations.
0080 %     maxLevel: highest pyramid level for center-surround.
0081 %     minDelta: minimum distance (levels) between center and surround.
0082 %     maxDelta: maximum distance (levels) between center and surround.
0083 %     mapLevel: pyramid level for all maps, including the saliency map.
0084 %
0085 % See also defaultLevelParams, centerSurround, winnerToImgCoords.
0086 %
0087 %
0088 % gaborParams - a structure with parameters for Gabor orientation filters.
0089 %       filterPeriod: the period of the filter in pixels.
0090 %         elongation: the ratio of length versus width.
0091 %         filterSize: the size of the filter in pixels.
0092 %             stddev: the standard deviation of the Gaussian envelope in pixels.
0093 %             phases: the phase angles to be used.
0094 %
0095 % See also defaultGaborParams, makeGaborFilter, gaborFilterMap, makeOrientationPyramid.
0096 %
0097 %
0098 % hueParams - describes 2d Gaussian color distribution in CIE space.
0099 %        muR: mean value in the CR direction.
0100 %       sigR: standard deviation in the CR direction.
0101 %        muG: mean value in the CG direction.
0102 %       sigG: standard deviation in the CG direction.
0103 %        rho: correlation coefficient between CR and CG.
0104 %
0105 % See also hueDistance, makeHuePyramid, skinHueParams.
0106 %
0107 %
0108 % saliencyData - a vector of structures for each feature with additional
0109 %                information from computing the saliency map.
0110 %      origImage: Image structure of the input image.
0111 %          label: the feature name.
0112 %            pyr: a vector of pyramids for this feature.
0113 %             FM: a vector of feature maps.
0114 %       csLevels: the center and surround levels used to
0115 %                 compute the feature maps from the pyramids.
0116 %             CM: the conspicuity map for this feature.
0117 %           date: time stamp.
0118 %
0119 % See also makeSaliencyMap, estimateShape, runSaliency.
0120 %
0121 %
0122 % shapeData - information about the shape of the attended regions.
0123 %       origImage: the Image structure for the source image.
0124 %          winner: the winning location in saliency map coordinates.
0125 %      winningMap: the map for the most salient feature at the winner location.
0126 %         iorMask: the mask used for shape-based inhibition of return.
0127 %       binaryMap: a binary map of the attended region.
0128 %    segmentedMap: the winning map segmented by the binary map.
0129 %        shapeMap: a smoothed version of segmentedMap.
0130 %            date: time stamp.
0131 %
0132 % See also estimateShape, shapeIOR, applyIOR, plotSalientLocation, runSaliency.
0133 %
0134 %
0135 % WTA - a winner-take-all neural network.
0136 %       sm: LIF neuron field for input from the saliency map.
0137 %      exc: excitatory LIF neurons field.
0138 %    inhib: inhibitory inter-neuron.
0139 %
0140 % See also initializeWTA, evolveWTA.
0141 %
0142 %
0143 % LIF - leaky integrate and fire neuron (field).
0144 %     timeStep: time step for integration (in sec).
0145 %        Eleak: leak potential (in V).
0146 %         Eexc: potential for excitatory channels (positive, in V).
0147 %         Einh: potential for inhibitory channels (negative, in V).
0148 %        Gleak: leak conductivity (in S).
0149 %         Gexc: conductivity of excitatory channels (in S).
0150 %         Ginh: conductivity of inhibitory channels (in S).
0151 %    GinhDecay: time constant for decay of inhibitory conductivity (in S).
0152 %       Ginput: input conductivity (in S).
0153 %      Vthresh: threshold potential for firing (in V).
0154 %            C: capacity (in F).
0155 %         time: current time (in sec).
0156 %            V: current membrane potential (in V) - can be an array for several neurons.
0157 %            I: current input current (in A) - can be an array for several neurons.
0158 %     DoesFire: neuron can (1) or cannot (0) fire.
0159 %
0160 % See also defaultLeakyIntFire, evolveLeakyIntFire, initializeWTA.
0161 %
0162 %
0163 %   LTUnetwork - a network of N linear threshold units.
0164 %    connections: N x N weight matrix, a sparse matrix.
0165 %     thresholds: 1 x N vector with thresholds for the units.
0166 %      input_idx: the indices of all input units in the network.
0167 %     output_idx: the indices of all output units in the network.
0168 %       numCells: the number of units.
0169 %          label: a text label fo the network.
0170 %
0171 % See also LTUsimulate, LTUsegmentMap, makeLTUsegmentNetwork.
0172 
0173 % This file is part of the SaliencyToolbox - Copyright (C) 2006-2007
0174 % by Dirk B. Walther and the California Institute of Technology.
0175 % See the enclosed LICENSE.TXT document for the license agreement.
0176 % More information about this project is available at:
0177 % http://www.saliencytoolbox.net
0178 
0179 more on;
0180 help(mfilename);
0181 more off;

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