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.
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;