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gaussian - returns a 1d Gaussian kernel. kernel = gaussian(peak,sigma,maxhw) Returns a 1d Gaussian kernel with peak as the value at the maximum and sigma as the standard deviation (in pixels). The half width (hw) of the kernel is determined by where the Gaussian drops off to 1 % of the peak value, but is bounded by maxhw (set to 0 for no bounding). The kernel will be of length: 2 * hw + 1. kernel = gaussian(peak,sigma,maxhw, treshPercent) Use threshPercent (in % of peak value) instead of 1 % to determine the half width.

- estimateShape estimateShape - estimates the shape of the attended proto-object region.
- maxNormalizeIterative maxNormalizeIterative - normalize data with the an iterative algorithm.

0001 % gaussian - returns a 1d Gaussian kernel. 0002 % 0003 % kernel = gaussian(peak,sigma,maxhw) 0004 % Returns a 1d Gaussian kernel with peak as the value 0005 % at the maximum and sigma as the standard deviation (in pixels). 0006 % The half width (hw) of the kernel is determined by where the 0007 % Gaussian drops off to 1 % of the peak value, but 0008 % is bounded by maxhw (set to 0 for no bounding). 0009 % The kernel will be of length: 2 * hw + 1. 0010 % 0011 % kernel = gaussian(peak,sigma,maxhw, treshPercent) 0012 % Use threshPercent (in % of peak value) instead of 1 % 0013 % to determine the half width. 0014 0015 % This file is part of the SaliencyToolbox - Copyright (C) 2006-2013 0016 % by Dirk B. Walther and the California Institute of Technology. 0017 % See the enclosed LICENSE.TXT document for the license agreement. 0018 % More information about this project is available at: 0019 % http://www.saliencytoolbox.net 0020 0021 function kernel = gaussian(peak,sigma,maxhw,varargin) 0022 0023 if isempty(varargin) 0024 threshPercent = 1; 0025 else 0026 threshPercent = varargin{1}; 0027 end 0028 0029 hw = floor(sigma * sqrt(-2 * log(threshPercent / 100))); 0030 0031 % cut the half width off if it is too large 0032 if ((maxhw > 0) & (hw > maxhw)) 0033 hw = maxhw; 0034 end 0035 0036 % get the right peak value (if peak = 0, normalize area to 1) 0037 if (peak == 0) 0038 peak = 1 / (sigma * sqrt(2*pi)); 0039 end 0040 0041 % build the kernel 0042 sig22 = -0.5 / (sigma * sigma); 0043 tmp = peak * exp(- [1:hw].^2 / (2*sigma*sigma)); 0044 kernel = [tmp(hw:-1:1) peak tmp];

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