Home > SaliencyToolbox > dataStructures.m

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.

  See also initializeGlobal, declareGlobal, debugMsg.


 Image - stores information about an image.
   filename: the filename.
       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'.
              IORdecay: decay rate of the inhibitive conductance responsible for inihibiiton
                        of return per simulation step of 0.1 ms.
         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).
        oriComputeType: 'efficient' (default) or 'full'
                        'efficient' only computes orientation filters for the levels that are
                                    actually going to be used in the center-surround computation
                       'full' computes the orientation filters for all levels
    visualizationStyle: style used for visualizing attended locations,
                        one of: 'Contour', 'ContrastModulate', 'None'.
         exclusionMask: struct of type map or 2d mask of numeric or logical type
                        regions where exclusionMask is ~= 0 are excluded from the saliency
                        computations by setting all feature maps to 0 in these areas. The
                        mask is automatically resized to the size of the feature maps.

 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 %
0010 %  See also initializeGlobal, declareGlobal, debugMsg.
0011 %
0012 %
0013 % Image - stores information about an image.
0014 %   filename: the filename.
0015 %       data: the image data (UINT8 or double)
0016 %             Each image structure has to contain the filename or the data
0017 %             field. It can have both.
0018 %       type: some text label.
0019 %       size: the size of the image.
0020 %       dims: the number of dimensions of the image (2 or 3).
0021 %       date: time stamp.
0022 %
0023 % See also initializeImage.
0024 %
0025 %
0026 % Map - 2d data structure with extra information.
0027 %     origImage: Image from which this map was computed.
0028 %         label: text label identying the map.
0029 %          data: 2d array with the map data.
0030 %          date: time stamp.
0031 %    parameters: parameters used for generating this map.
0032 %
0033 % See also displayMap, displayMaps.
0034 %
0035 %
0036 % Pyramid - a multi-resolution pyramid for a particular feature.
0037 %    origImage: the source image.
0038 %        label: text label denoting the feature.
0039 %         type: type of subsampling, one of: 'dyadic','sqrt2','TopDown'.
0040 %       levels: vector of maps containing the levels of this pyramid.
0041 %         date: time stamp.
0042 %
0043 % See also makeFeaturePyramids, displayPyramid, runSaliency.
0044 %
0045 %
0046 % SaliencyParams - set of parameters used for generating a saliency map.
0047 %               foaSize: size of the focus of attention for disk-IOR.
0048 %           pyramidType: 'dyadic' or 'sqrt2'.
0049 %              features: cell array of the features to be used for saliency computation
0050 %                        possible values: 'Color', 'Intensities', 'Orientations', 'Skin','TopDown'.
0051 %               weights: vector of weights for each feature (same length as features)
0052 %               IORtype: type of inhibition of return, one of: 'shape','disk','None'.
0053 %             shapeMode: one of: 'None','shapeSM','shapeCM','shapeFM','shapePyr'.
0054 %           levelParams: structure with pyramid level parameters.
0055 %              normtype: Map normalization type, one of: 'None','LocalMax','Iterative'.
0056 %               numIter: Number of iterations for 'Iterative' normtype.
0057 %             useRandom: Use random jitter (1) or not (0) for converting coodinates.
0058 %    segmentComputeType: Method for shape segmentation, one of: 'Fast','LTU'.
0059 %              IORdecay: decay rate of the inhibitive conductance responsible for inihibiiton
0060 %                        of return per simulation step of 0.1 ms.
0061 %         smOutputRange: saliency map output in Amperes (1e-9).
0062 %             noiseAmpl: amplitude of random noise (1e-17).
0063 %            noiseConst: amplitude of contant noise (1e-14).
0064 %           gaborParams: structure with parameters for Gabor orientation filters.
0065 %             oriAngles: vector with orientation angles (in degrees).
0066 %        oriComputeType: 'efficient' (default) or 'full'
0067 %                        'efficient' only computes orientation filters for the levels that are
0068 %                                    actually going to be used in the center-surround computation
0069 %                       'full' computes the orientation filters for all levels
0070 %    visualizationStyle: style used for visualizing attended locations,
0071 %                        one of: 'Contour', 'ContrastModulate', 'None'.
0072 %         exclusionMask: struct of type map or 2d mask of numeric or logical type
0073 %                        regions where exclusionMask is ~= 0 are excluded from the saliency
0074 %                        computations by setting all feature maps to 0 in these areas. The
0075 %                        mask is automatically resized to the size of the feature maps.
0076 %
0077 % See also diskIOR, makeGaussianPyramid, makeSaliencyMap, applyIOR, estimateShape,
0078 %          centerSurround, maxNormalize, winnerToImgCoords, makeGaborFilter,
0079 %          defaultGaborParams, defaultLevelParams, plotSalientLocation.
0080 %
0081 %
0082 % levelParams - a structure with parameters for pyramid levels for
0083 %               center-surround operations
0084 %     minLevel: lowest pyramid level (starting at 1) for center-surround computations.
0085 %     maxLevel: highest pyramid level for center-surround.
0086 %     minDelta: minimum distance (levels) between center and surround.
0087 %     maxDelta: maximum distance (levels) between center and surround.
0088 %     mapLevel: pyramid level for all maps, including the saliency map.
0089 %
0090 % See also defaultLevelParams, centerSurround, winnerToImgCoords.
0091 %
0092 %
0093 % gaborParams - a structure with parameters for Gabor orientation filters.
0094 %       filterPeriod: the period of the filter in pixels.
0095 %         elongation: the ratio of length versus width.
0096 %         filterSize: the size of the filter in pixels.
0097 %             stddev: the standard deviation of the Gaussian envelope in pixels.
0098 %             phases: the phase angles to be used.
0099 %
0100 % See also defaultGaborParams, makeGaborFilter, gaborFilterMap, makeOrientationPyramid.
0101 %
0102 %
0103 % hueParams - describes 2d Gaussian color distribution in CIE space.
0104 %        muR: mean value in the CR direction.
0105 %       sigR: standard deviation in the CR direction.
0106 %        muG: mean value in the CG direction.
0107 %       sigG: standard deviation in the CG direction.
0108 %        rho: correlation coefficient between CR and CG.
0109 %
0110 % See also hueDistance, makeHuePyramid, skinHueParams.
0111 %
0112 %
0113 % saliencyData - a vector of structures for each feature with additional
0114 %                information from computing the saliency map.
0115 %      origImage: Image structure of the input image.
0116 %          label: the feature name.
0117 %            pyr: a vector of pyramids for this feature.
0118 %             FM: a vector of feature maps.
0119 %       csLevels: the center and surround levels used to
0120 %                 compute the feature maps from the pyramids.
0121 %             CM: the conspicuity map for this feature.
0122 %           date: time stamp.
0123 %
0124 % See also makeSaliencyMap, estimateShape, runSaliency.
0125 %
0126 %
0127 % shapeData - information about the shape of the attended regions.
0128 %       origImage: the Image structure for the source image.
0129 %          winner: the winning location in saliency map coordinates.
0130 %      winningMap: the map for the most salient feature at the winner location.
0131 %         iorMask: the mask used for shape-based inhibition of return.
0132 %       binaryMap: a binary map of the attended region.
0133 %    segmentedMap: the winning map segmented by the binary map.
0134 %        shapeMap: a smoothed version of segmentedMap.
0135 %            date: time stamp.
0136 %
0137 % See also estimateShape, shapeIOR, applyIOR, plotSalientLocation, runSaliency.
0138 %
0139 %
0140 % WTA - a winner-take-all neural network.
0141 %       sm: LIF neuron field for input from the saliency map.
0142 %      exc: excitatory LIF neurons field.
0143 %    inhib: inhibitory inter-neuron.
0144 %
0145 % See also initializeWTA, evolveWTA.
0146 %
0147 %
0148 % LIF - leaky integrate and fire neuron (field).
0149 %     timeStep: time step for integration (in sec).
0150 %        Eleak: leak potential (in V).
0151 %         Eexc: potential for excitatory channels (positive, in V).
0152 %         Einh: potential for inhibitory channels (negative, in V).
0153 %        Gleak: leak conductivity (in S).
0154 %         Gexc: conductivity of excitatory channels (in S).
0155 %         Ginh: conductivity of inhibitory channels (in S).
0156 %    GinhDecay: time constant for decay of inhibitory conductivity (in S).
0157 %       Ginput: input conductivity (in S).
0158 %      Vthresh: threshold potential for firing (in V).
0159 %            C: capacity (in F).
0160 %         time: current time (in sec).
0161 %            V: current membrane potential (in V) - can be an array for several neurons.
0162 %            I: current input current (in A) - can be an array for several neurons.
0163 %     DoesFire: neuron can (1) or cannot (0) fire.
0164 %
0165 % See also defaultLeakyIntFire, evolveLeakyIntFire, initializeWTA.
0166 %
0167 %
0168 %   LTUnetwork - a network of N linear threshold units.
0169 %    connections: N x N weight matrix, a sparse matrix.
0170 %     thresholds: 1 x N vector with thresholds for the units.
0171 %      input_idx: the indices of all input units in the network.
0172 %     output_idx: the indices of all output units in the network.
0173 %       numCells: the number of units.
0174 %          label: a text label fo the network.
0175 %
0176 % See also LTUsimulate, LTUsegmentMap, makeLTUsegmentNetwork.
0177 
0178 % This file is part of the SaliencyToolbox - Copyright (C) 2006-2013
0179 % by Dirk B. Walther and the California Institute of Technology.
0180 % See the enclosed LICENSE.TXT document for the license agreement.
0181 % More information about this project is available at:
0182 % http://www.saliencytoolbox.net
0183 
0184 more on;
0185 help(mfilename);
0186 more off;

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