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github | santhosh-kumar/ContextualMultiCameraTracker-master | toolboxGenDoc.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/toolboxGenDoc.m | 3,770 | utf_8 | dfd95e962061a5afd392f4549d3ef75b | function toolboxGenDoc
% Generate documentation, must run from dir toolbox.
%
% 1) Make sure to update and run toolboxUpdateHeader.m
% 2) Update history.txt appropriately, including w current version
% 3) Update overview.html file with the version/date/link to zip:
% edit external/m2html/templates/frame-piotr... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | toolboxHeader.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/toolboxHeader.m | 2,519 | utf_8 | 7530495be10750dc20e944da853d9793 | function [y1,y2] = toolboxHeader( x1, x2, x3, prm )
% One line description of function (will appear in file summary).
%
% General commments explaining purpose of function [width is 75
% characters]. There may be multiple paragraphs. In special cases some or
% all of these guidelines may need to be broken.
%
% Ne... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | mdot.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/m2html/mdot.m | 2,516 | utf_8 | 34a14428c433e118d1810e23f5a6caf5 | function mdot(mmat, dotfile,f)
%MDOT - Export a dependency graph into DOT language
% MDOT(MMAT, DOTFILE) loads a .mat file generated by M2HTML using option
% ('save','on') and writes an ascii file using the DOT language that can
% be drawn using <dot> or <neato> .
% MDOT(MMAT, DOTFILE,F) builds the graph containing... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | m2html.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/m2html/m2html.m | 49,063 | utf_8 | 472047b4c36a4f8b162012840e31b59b | function m2html(varargin)
%M2HTML - Documentation Generator for Matlab M-files and Toolboxes in HTML
% M2HTML by itself generates an HTML documentation of the Matlab M-files found
% in the direct subdirectories of the current directory. HTML files are
% written in a 'doc' directory (created if necessary). All the o... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | doxysearch.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/m2html/private/doxysearch.m | 7,724 | utf_8 | 8331cde8495f34b86aef8c18656b37f2 | function result = doxysearch(query,filename)
%DOXYSEARCH Search a query in a 'search.idx' file
% RESULT = DOXYSEARCH(QUERY,FILENAME) looks for request QUERY
% in FILENAME (Doxygen search.idx format) and returns a list of
% files responding to the request in RESULT.
%
% See also DOXYREAD, DOXYWRITE
% Copyright (C)... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | doxywrite.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/m2html/private/doxywrite.m | 3,584 | utf_8 | 3255d8f824957ebc173dde374d0f78af | function doxywrite(filename, kw, statinfo, docinfo)
%DOXYWRITE Write a 'search.idx' file compatible with DOXYGEN
% DOXYWRITE(FILENAME, KW, STATINFO, DOCINFO) writes file FILENAME
% (Doxygen search.idx. format) using the cell array KW containing the
% word list, the sparse matrix (nbword x nbfile) with non-null value... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | doxyread.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/m2html/private/doxyread.m | 3,093 | utf_8 | 3152e7d26bf7ac64118be56f72832a20 | function [statlist, docinfo] = doxyread(filename)
%DOXYREAD Read a 'search.idx' file generated by DOXYGEN
% STATLIST = DOXYREAD(FILENAME) reads FILENAME (Doxygen search.idx
% format) and returns the list of keywords STATLIST as a cell array.
% [STATLIST, DOCINFO] = DOXYREAD(FILENAME) also returns a cell array
% con... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | imwrite2split.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/imwrite2split.m | 1,664 | utf_8 | 8fa6eef9378b3b9aa633d6c096cd78f7 | % Writes/reads a large set of images into/from multiple directories.
%
% This is useful since certain OS handle very large directories (of say
% >20K images) rather poorly (I'm talking to you Bill). Thus, can take
% 100K images, and write into 5 separate directories, then read them back
% in.
%
% USAGE
% I = ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | playmovies.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/playmovies.m | 1,997 | utf_8 | 6d94553879ed29dca7238d26459ec685 | % [4D] shows R videos simultaneously as a movie.
%
% Plays a movie.
%
% USAGE
% playmovies( I, [fps], [loop] )
%
% INPUTS
% I - MxNxTxR or MxNx1xTxR or MxNx3xTxR array (if MxNxT calls
% playmovie)
% fps - [100] maximum number of frames to display per second use
% fps==0 to ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | pca_apply_large.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/pca_apply_large.m | 2,132 | utf_8 | daf33ba3f73412c5d5b488d89b7cc495 | % Wrapper for pca_apply that allows for application to large X.
%
% Wrapper for pca_apply that splits and processes X in parts, this may be
% useful if processing cannot be done fully in parallel because of memory
% constraints. See pca_apply for usage.
%
% USAGE
% same as pca_apply
%
% INPUTS
% same as pca... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | montages2.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/montages2.m | 2,335 | utf_8 | 3ff14e5c538db6af4c9e1c99144d7c15 | % MONTAGES2 [4D] Used to display R sets of T images each.
%
% Displays one montage (see montage2) per row. Each of the R image sets is
% flattened to a single long image by concatenating the T images in the
% set. Alternative to montages.
%
% USAGE
% varargout = montages2( IS, [montage2prms], [padSiz] )
%
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | filter_gauss_1D.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/filter_gauss_1D.m | 1,178 | utf_8 | 42acb7f8ac4ce94b6dc1dabe1e51e313 | % 1D Gaussian filter.
%
% Equivalent to (but faster then):
% f = fspecial('Gaussian',[2*r+1,1],sigma);
% f = filter_gauss_nD( 2*r+1, r+1, sigma^2 );
%
% USAGE
% f = filter_gauss_1D( r, sigma, [show] )
%
% INPUTS
% r - filter size=2r+1, if r=[] -> r=ceil(2.25*sigma)
% sigma - standard deviation o... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | clfEcoc.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/clfEcoc.m | 1,539 | utf_8 | 3cb7110d53d7eefcca505365b078fe8e | function clf = clfEcoc(p,clfInit,clfparams,nclasses,use01targets)
% Wrapper for ecoc that makes ecoc compatible with nfoldxval.
%
% Requires the SVM toolbox by Anton Schwaighofer.
%
% USAGE
% clf = clfEcoc(p,clfInit,clfparams,nclasses,use01targets)
%
% INPUTS
% p - data dimension
% clfInit ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | getargs.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/getargs.m | 3,550 | utf_8 | b8ee235c28195894f0743b6cd00fd609 | % Utility to process parameter name/value pairs.
%
% DEPRECATED -- ONLY USED BY KMEANS2? SHOULD BE REMOVED.
% USE GETPARAMDEFAULTS INSTEAD.
%
% Based on code fromt Matlab Statistics Toolobox's "private/statgetargs.m"
%
% [EMSG,A,B,...]=GETARGS(PNAMES,DFLTS,'NAME1',VAL1,'NAME2',VAL2,...)
% accepts a cell array ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | normxcorrn_fg.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/normxcorrn_fg.m | 2,771 | utf_8 | c0817b10bbc5d1793efad5fa7b4932ac | % Normalized n-dimensional cross-correlation with a mask.
%
% Similar to normxcorrn, except takes an additional argument that specifies
% a figure ground mask for the T. That is T_fg must be of the same
% dimensions as T, with each entry being 0 or 1, where zero specifies
% regions to ignore (the ground) and 1 sp... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | makemovie.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/makemovie.m | 1,313 | utf_8 | 7cadf737855cee5cb9a336e1204773c4 | % [3D] Used to convert a stack of T images into a movie.
%
% To display same data statically use montage.
%
% USAGE
% M = makemovies( IS )
%
% INPUTS
% IS - MxNxT or MxNx1xT or MxNx3xT array of movies.
%
% OUTPUTS
% M - resulting movie
%
% EXAMPLE
% load( 'images.mat' );
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | localsum_block.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/localsum_block.m | 845 | utf_8 | d420d188aa320337183491498c7cc483 | % Calculates the sum in non-overlapping blocks of I of size dims.
%
% Similar to localsum except gets sum in non-overlapping windows.
% Equivalent to doing localsum, and then subsampling (except more
% efficient).
%
% USAGE
% I = localsum_block( I, dims )
%
% INPUTS
% I - matrix to compute sum over
%... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | imrotate2.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/imrotate2.m | 1,367 | utf_8 | 21148eb1e941255d74de56b5cb8994b1 | % Custom version of imrotate that demonstrates use of apply_homography.
%
% Works exactly the same as imrotate. For usage see imrotate.
%
% USAGE
% IR = imrotate2( I, angle, [method], [bbox] )
%
% INPUTS
% I - 2D image [converted to double]
% angle - angle to rotate in degrees
% method - ['linea... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | imSubsResize.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/imSubsResize.m | 1,379 | utf_8 | 7bcc46113f2b8619d539a20ecb5a1835 | % Resizes subs by resizVals.
%
% Resizes subs in subs/vals image representation by resizVals.
%
% This essentially replaces each sub by sub.*resizVals. The only subtlety
% is that in images the leftmost sub value is .5, so for example when
% resizing by a factor of 2, the first pixel is replaced by 2 pixels and ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | imtranslate.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/imtranslate.m | 1,221 | utf_8 | 8a46326f7c0b520a89e2c4a153118ec9 | % Translate an image to subpixel accuracy.
%
% Note that for subplixel accuracy cannot use nearest neighbor interp.
%
% USAGE
% IR = imtranslate( I, dx, dy, [method], [bbox] )
%
% INPUTS
% I - 2D image [converted to double]
% dx - x translation (right)
% dy - y translation (up)
% method ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | randperm2.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/randperm2.m | 1,444 | utf_8 | b8dc96688b2afddb3bd486803d3847b5 | % Returns a random permutation of integers.
%
% randperm2(n) is a random permutation of the integers from 1 to n. For
% example, randperm2(6) might be [2 4 5 6 1 3]. randperm2(n,k) is only
% returns the first k elements of the permuation, so for example
% randperm2(6) might be [2 4]. This is a faster version of ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | apply_homography.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/apply_homography.m | 3,676 | utf_8 | 18c79558e14e422d02c755d8363c7460 | % Applies the homography defined by H on the image I.
%
% Takes the center of the image as the origin, not the top left corner.
% Also, the coordinate system is row/ column format, so H must be also.
%
% The bounding box of the image is set by the BBOX argument, a string that
% can be 'loose' (default) or 'crop'.... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | pca_apply.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/pca_apply.m | 2,506 | utf_8 | 4f38cdb1a3375943269e24dc6be6af65 | % Companion function to pca.
%
% Use pca to retrieve the principal components U and the mean mu from a
% set fo vectors X1 via [U,mu,vars] = pca(X1). Then given a new
% vector x, use y = pca_apply( x, U, mu, vars, k ) to get the first k
% coefficients of x in the space spanned by the columns of U. See pca for
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | mode2.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/deprecated/mode2.m | 765 | utf_8 | f6b3681635cfe16059c5483214fb9814 | % Returns the mode of a vector.
%
% Was mode not part of Matlab before?
%
% USAGE
% y = mode2( x )
%
% INPUTS
% x - vector of integers
%
% OUTPUTS
% y - mode
%
% EXAMPLE
% x = randint2( 1, 10, [1 3] )
% mode(x), mode2( x )
%
% See also MODE
% Piotr's Image&Video Toolbox Version 1.5
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | savefig.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/external/other/savefig.m | 13,374 | utf_8 | b8aace9bef044800b8fc876fde5bf33f | function savefig(fname, varargin)
% Usage: savefig(filename, fighdl, options)
%
% Saves a pdf, eps, png, jpeg, and/or tiff of the contents of the fighandle's (or current) figure.
% It saves an eps of the figure and the uses Ghostscript to convert to the other formats.
% The result is a cropped, clean picture. There a... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | dirSynch.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/matlab/dirSynch.m | 4,760 | utf_8 | 98722043acf461badcbf811797e8f35c | function dirSynch( root1, root2, showOnly, flag, ignDate )
% Synchronize two directory trees (or show differences between them).
%
% If a file or directory 'name' is found in both tree1 and tree2:
% 1) if 'name' is a file in both the pair is considered the same if they
% have identical size and identical date... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | plotRoc.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/matlab/plotRoc.m | 5,407 | utf_8 | 6de0cb3305bb49d76673c90ad10d3f43 | function [h,miss,stds] = plotRoc( D, varargin )
% Function for display of rocs (receiver operator characteristic curves).
%
% Display roc curves. Consistent usage ensures uniform look for rocs. The
% input D should have n rows, each of which is of the form:
% D = [falsePosRate truePosRate]
% D is generated, for ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | simpleCache.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/matlab/simpleCache.m | 4,293 | utf_8 | 22f799042e5c852998fa3462c9363fc7 | function varargout = simpleCache( op, cache, varargin )
% A simple cache that can be used to store results of computations.
%
% Can save and retrieve arbitrary values using a vector (includnig char
% vectors) as a key. Especially useful if a function must perform heavy
% computation but is often called with the sa... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | tpsInterpolate.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/matlab/tpsInterpolate.m | 1,760 | utf_8 | 718883df87f2cad99fe591d11b8693db | function [xsR,ysR] = tpsInterpolate( warp, xs, ys, show )
% Apply warp (obtained by tpsGetWarp) to a set of new points.
%
% USAGE
% [xsR,ysR] = tpsInterpolate( warp, xs, ys, [show] )
%
% INPUTS
% warp - [see tpsGetWarp] bookstein warping parameters
% xs, ys - points to apply warp to
% show - [1] ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | checkNumArgs.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/matlab/checkNumArgs.m | 3,968 | utf_8 | 262a28a0ba12c107b0244a10b38606ae | function [ x, er ] = checkNumArgs( x, siz, intFlag, signFlag )
% Helper utility for checking numeric vector arguments.
%
% Runs a number of tests on the numeric array x. Tests to see if x has all
% integer values, all positive values, and so on, depending on the values
% for intFlag and signFlag. Also tests to se... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | fevalDistr.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/matlab/fevalDistr.m | 12,765 | utf_8 | 3f490cb79ce1134078e2a18e6a47afba | function [out,res] = fevalDistr( funNm, jobs, varargin )
% Wrapper for embarrassingly parallel function evaluation.
%
% Runs "r=feval(funNm,jobs{i}{:})" for each job in a parallel manner. jobs
% should be a cell array of length nJob and each job should be a cell array
% of parameters to pass to funNm. funNm must b... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | medfilt1m.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/filters/medfilt1m.m | 3,138 | utf_8 | 0ae9cc23ba8aec631160413b125a39a2 | function y = medfilt1m( x, r, z )
% One-dimensional adaptive median filtering with missing values.
%
% Applies a width s=2*r+1 one-dimensional median filter to vector x, which
% may contain missing values (elements equal to z). If x contains no
% missing values, y(j) is set to the median of x(j-r:j+r). If x contai... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | FbMake.m | .m | ContextualMultiCameraTracker-master/libs/toolbox/filters/FbMake.m | 6,962 | utf_8 | de8baf5b056d6d153f8ae0755ade2de5 | function FB = FbMake( dim, flag, show )
% Various 1D/2D/3D filterbanks (hardcoded).
%
% USAGE
% FB = FbMake( dim, flag, [show] )
%
% INPUTS
% dim - dimension
% flag - controls type of filterbank to create
% - if d==1
% 1: gabor filter bank for spatiotemporal stuff
% - i... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | drawEdge.m | .m | ContextualMultiCameraTracker-master/libs/geom2d/libGeom2d/geom2d/drawEdge.m | 3,223 | utf_8 | 6fb4f10c921d6882550b0d836ae20dc4 | function varargout = drawEdge(varargin)
%DRAWEDGE Draw an edge given by 2 points
%
% drawEdge(x1, y1, x2, y2);
% draw an edge between the points (x1 y1) and (x2 y2).
%
% drawEdge([x1 y1 x2 y2]) ;
% drawEdge([x1 y1], [x2 y2]);
% specify data either as bundled edge, or as 2 points
%
% The functi... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | enclosingCircle.m | .m | ContextualMultiCameraTracker-master/libs/geom2d/libGeom2d/geom2d/enclosingCircle.m | 1,877 | utf_8 | cc42da36eb019ff067ae5a02b00131de | function circle = enclosingCircle(pts)
%ENCLOSINGCIRCLE Find the minimum circle enclosing a set of points.
%
% CIRCLE = enclosingCircle(POINTS);
% compute cirlce CIRCLE=[xc yc r] which enclose all points POINTS given
% as an [Nx2] array.
%
%
% Rewritten from a file from
% Yazan Ahed (yash78@g... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | polynomialCurveSetFit.m | .m | ContextualMultiCameraTracker-master/libs/geom2d/libGeom2d/polynomialCurves2d/polynomialCurveSetFit.m | 5,584 | utf_8 | 8dc90a6635bc63b29724ba33fb521305 | function [coefs lblBranches] = polynomialCurveSetFit(seg, varargin)
%POLYNOMIALCURVESETFIT Fit a set of polynomial curves to a segmented image
%
% COEFS = polynomialCurveSetFit(IMG);
% COEFS = polynomialCurveSetFit(IMG, DEG);
% Result is a cell array of matrices. Each matrix is DEG+1-by-2, and
% contains ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | polynomialCurvePosition.m | .m | ContextualMultiCameraTracker-master/libs/geom2d/libGeom2d/polynomialCurves2d/polynomialCurvePosition.m | 2,965 | utf_8 | e8933d9b90e0b043fc8392746e0be496 | function pos = polynomialCurvePosition(tBounds, varargin)
%POLYNOMIALCURVEPOSITION Compute position on a curve for a given length
%
% POS = polynomialCurvePosition(T, XCOEF, YCOEF, L)
% XCOEF and YCOEF are row vectors of coefficients, in the form:
% [a0 a1 a2 ... an]
% T is a 1x2 row vector, containin... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | glob.m | .m | ContextualMultiCameraTracker-master/libs/lightspeed/glob.m | 3,726 | utf_8 | 0cfc427836c4ab484b88fa5bbf1ae471 | function [names,isdirs] = glob(pattern,prefix)
%GLOB Filename expansion via wildcards.
% GLOB(PATTERN) returns a cell array of file/directory names which match the
% PATTERN.
% [NAMES,ISDIRS] = GLOB(PATTERN) also returns a logical vector indicating
% which are directories.
%
% Two types of wildcards are su... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | flops_pow.m | .m | ContextualMultiCameraTracker-master/libs/lightspeed/flops_pow.m | 1,432 | utf_8 | 5843823015471636d6d1b205800ac1fb | function f = flops_pow(a)
% FLOPS_POW Flops for raising to real power.
% FLOPS_POW(A) returns the number of flops for (X .^ A) where X is scalar.
% Powers like 0, 1, 2, and 1/2 are handled specially.
flops_div = 8;
flops_sqrt = 8;
if nargin < 1
a = 0.1;
end
f = 0;
if a < 0
f = f + flops_div;
a = ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | duplicated.m | .m | ContextualMultiCameraTracker-master/libs/lightspeed/duplicated.m | 1,440 | utf_8 | af1b5fe0787eb874aa6ca5df411128be | function d = duplicated(x)
%DUPLICATED Find duplicated rows.
% DUPLICATED(x) returns a vector d such that d(i) = 1 if x(i,:) is a
% duplicate of an earlier row.
%
% Examples:
% duplicated([2 7 8 7 1 2 8]') = [0 0 0 1 0 1 1]'
% duplicated([0 0 1 1 0; 0 1 0 1 1]') = [0 0 0 0 1]'
% duplicated(eye(100))
% dupli... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | subsasgn.m | .m | ContextualMultiCameraTracker-master/libs/lightspeed/@mutable/subsasgn.m | 1,488 | utf_8 | 44c7dae848f5b621b638053c1b231e87 | function mut = subsasgn(mut,index,v)
% Written by Tom Minka
% (c) Microsoft Corporation. All rights reserved.
subsasgnJava(mut.obj,index,v,mut.cl);
function subsasgnJava(jv,index,v,cl)
if nargin < 4
% class(jv) is expensive, so we do it only once
cl = class(jv);
end
if strcmp(cl,'java.util.Hashtabl... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | subsref.m | .m | ContextualMultiCameraTracker-master/libs/lightspeed/@mutable/subsref.m | 1,686 | utf_8 | 9b67e3386d0641a031d3e3d3761a81dc | function v = subsref(mut,index)
% Written by Tom Minka
% (c) Microsoft Corporation. All rights reserved.
v = subsrefJava(mut.obj,index,mut.cl);
function v = subsrefJava(jv,index,cl)
if nargin < 3
% class(jv) is expensive, so we do it only once
cl = class(jv);
end
wantcell = 0;
if strcmp(cl,'java.u... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | test_sameobject.m | .m | ContextualMultiCameraTracker-master/libs/lightspeed/tests/test_sameobject.m | 263 | utf_8 | 8705f5d46d51edcdc06e7272b4504f75 | function test_sameobject
% Result should be 1 in both cases below.
a = rand(4);
b = a;
if sameobject(a,b) ~= 1
error('failed');
end
if helper(a,a) ~= 1
error('failed');
end
disp('Test passed.')
function x = helper(a,b)
x = sameobject(a,b);
|
github | santhosh-kumar/ContextualMultiCameraTracker-master | meanshiftSpatial.m | .m | ContextualMultiCameraTracker-master/libs/lib_boosting/meanshiftSpatial.m | 1,503 | utf_8 | 19c3db4675c2f7ed1bdc33d3afc154fd | function [mode] = meanshiftSpatial(data, h, epsilon, init_pt, w, iterations)
[d N] = size(data);
eps2 = epsilon*epsilon;
mode = ones(d, 1);
if( size(init_pt) ~= size(mode) )
error('Not the proper dimension');
end
x = init_pt;
for iter = 1:iterations
[m, s] = mean_shift_iteration(x, da... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | selectBestRegressionStump.m | .m | ContextualMultiCameraTracker-master/libs/lib_boosting/selectBestRegressionStump.m | 1,334 | utf_8 | da57015e6f9d7589cb89a14b7efee7fb | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function selects the best regression stump
%
% [th, a , b] = fitRegressionStump(x, z);
% z = a * (x>th) + b;
% where (a,b,th) are so that it minimizes the weighted error:
% error = sum(w * |z - (a*(x>th) + b)|^2) / sum(w)... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | plot.m | .m | ContextualMultiCameraTracker-master/libs/@kde/plot.m | 7,653 | utf_8 | f780548e87d0f1875ec9268afce4fd9d | function H=plot(x,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% KDE plotting function
%
% plot(kde) -- plot a KDE with various features.
% plot(kde,style) -- style is of the form
% plot(kde,dim,style) -- [STR1,STR2,...] where
%
% style is of the form [STR1 ST... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | entropyGrad.m | .m | ContextualMultiCameraTracker-master/libs/@kde/entropyGrad.m | 1,006 | utf_8 | a482a4db37c9545ec0c790ded65aca1c | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% err = entropyGrad(npd,estType)
% Compute gradient of an entropy estimate for the npde
%
% entType is one of:
% ISE : integrated squared error from uniform estimate
% RS,LLN : law of large numbers resubsti... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | modes.m | .m | ContextualMultiCameraTracker-master/libs/@kde/modes.m | 3,423 | utf_8 | a1561f4327e4c415e1afd6892fd87c0a | function [modeList,attr] = modes(dens,start)
%
% [modes,assoc] = modes(kde [,init]) -- Find modes of a KDE via fixed point iter. scheme
% options:
% init -- initial locations for search (default is kde's kernel centers)
% returns:
% modes -- list of estimated mode locations
% assoc -- which mode each initi... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | quantize.m | .m | ContextualMultiCameraTracker-master/libs/@kde/quantize.m | 728 | utf_8 | da02b55a43079674304fd19db18da126 | function p = quantize(p,R,minV,maxV,minS,maxS)
%
% p = quantize(p,R,type) -- "quantize" elements of KDE p to R bits
%
%p.centers = round(1000*p.centers)/1000;
%p.means = round(1000*p.means)/1000;
%p.ranges = round(1000*p.ranges)/1000;
%p.bandwidth = ceil(10000*p.bandwidth)/10000;
p.centers = roundVals(p.ce... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | evalIFGT.m | .m | ContextualMultiCameraTracker-master/libs/@kde/evalIFGT.m | 7,222 | utf_8 | ef0bcd2b59b2c10f6427f8e75ba67a2e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% evalIFGT Evaluate the density estimate using the "improved" Fast Gauss Transform
%
% [e,b] = evalIFGT(X,Y,N [,Nc,rC]) -- eval likelihood ("e") of the points Y under
% the density estimate X using N coefficient... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | joinTrees.m | .m | ContextualMultiCameraTracker-master/libs/@kde/joinTrees.m | 6,414 | utf_8 | 749cd7423770167e50c916245f2e8d2a | function t1 = joinTrees(t1, t2, alpha)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% t12 = joinTrees(t1, t2, alpha)
% create a new KD-tree with t1 and t2 as the children of the root
% The t1 subtree recieves weight alpha; the t2 subtree has wt. 1-alpha
%
%%%%%%%%%%%%%%%%%%%%%... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | maxlogerr.m | .m | ContextualMultiCameraTracker-master/libs/@kde/maxlogerr.m | 2,415 | utf_8 | e64b1877c0870706f1d99ce2085e21ad | function [maxVal,location] = logerr(p,q)
%
% modes = logerr(p,q) -- Find location of max. log-error between p&q
%
%
%
% Copyright (C) 2003 Alexander Ihler; distributable under GPL -- see README.txt
start = [getPoints(p),getPoints(q)];
tol=1e-4; % set tolerance values etc.
max_it=1000;
minDistance = 1e-2;
... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | klGrad.m | .m | ContextualMultiCameraTracker-master/libs/@kde/klGrad.m | 3,382 | utf_8 | 6061ba6101e34870ce76b5bad2da6097 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [err1,err2]=klGrad(dens1,dens2,estType)
% Compute gradient of a KL-divergence estimate, D(dens1 || dens2);
% estType is one of:
% ise : integrated squared error from uniform estimate (not yet implemented)
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | reduce.m | .m | ContextualMultiCameraTracker-master/libs/@kde/reduce.m | 8,009 | utf_8 | 5d3b50cda6be10c92128197ef2e28b74 | function [q,o2,o3] = reduce(p,type,varargin)
%
% q = reduce(p,'type',[options]) -- "Reduce" a KDE, so that it requires fewer
% kernels but has similar representative power (better than just resampling)
%
% 'type' is one of:
% 'mscale' -- "Multiscale data condensation" method of Mitra et al. PAMI '02
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | encode.m | .m | ContextualMultiCameraTracker-master/libs/@kde/encode.m | 2,845 | utf_8 | a122889765f9743426006390803a8ded | function C = encode(p,R)
%
% Compute vector of transmit costs for each stage of the KD-tree
%
N = getNpts(p); bw = getBW(p,1);
if (size(p.bandwidth,2) > 2*N)
error('Encoding of variable bandwidths not yet supported...');
end;
if (any( abs(getWeights(p) - 1/N) > 2*eps ))
error('Encoding of variable weights not ye... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | evalFGT.m | .m | ContextualMultiCameraTracker-master/libs/@kde/evalFGT.m | 6,928 | utf_8 | ea5f34be8bac0228188768426a5c0bde | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% evalIFGT Evaluate the density estimate using the (original) Fast Gauss Transform
%
% [e,b] = evalFGT(X,Y,N [,Nc,rC]) -- eval likelihood ("e") of the points Y under
% the density estimate X using N coeffic... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | ksize.m | .m | ContextualMultiCameraTracker-master/libs/@kde/ksize.m | 4,999 | utf_8 | cc58ac2721b998a18def3388ce16dc98 | function npd = ksize(npd,type,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% KSIZE Find optimal kernel size for kernel density estimates
%
% Q=KSIZE(P) returns a KDE with the same points and type as "P", but whose
% bandwidth has been determined by one of ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | prodSampleImportGauss.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/prodSampleImportGauss.m | 1,977 | utf_8 | 3db8a195988c137f702d1a0324c1cc68 | function [ptsS, wtsS] = prodSampleImportGaussian(npds,Npts,anFns,anParams,overSamp,type)
%
% Gaussian-approximation-based importance sampling (private function)
%
% See Ihler,Sudderth,Freeman,&Willsky, "Efficient multiscale sampling from products
% of Gaussian mixtures", in Proc. Neural Information Proces... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | randKernel.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/randKernel.m | 1,689 | utf_8 | aa78a3f09fb2be65647c3960caa3db3f | function samples = randKernel(N,M,type)
%
% samples = randKernel(N,M,type) -- Draw samples from a kernel of the
% given type, with bandwidth 1; for bw!=1,
% eg bw=getBW(dens,ind), use B.*randKernel(N,M,type)
%
% Copyright (C) 2003 Alexander Ihler; distributable und... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | reduceSolveM.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/reduceSolveM.m | 13,387 | utf_8 | 3a1291074803b254aa65ad998cd89a2f | %
% Internal routines for solving the quadratic minimization problem
% occurring for "reduced set density estimation" (RSDE)
% implemented by the function "@kde/reduce.m"
%
% Code by (a) Chao He and Mark Girolami (SMO, Mult)
% (b) Yinyu Ye (QP)
%
function alpha = reduceSolve(Q,D,type)
switch(type)
c... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | ksizeLSCV.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/ksizeLSCV.m | 1,124 | utf_8 | 655871b6248384de32bb43946219d78f | function h = ksizeLSCV(npd)
% "Least-Squares Cross Validation" estimate (Silverman)
%
% Copyright (C) 2005 Alexander Ihler; distributable under GPL -- see README.txt
% hROT = ksizeROT(npd);
% npd = kde(getPoints(npd),hROT,getWeights(npd),getType(npd));
% h = golden(npd,@nLSCV,.1,1,30,1e-2);
% h = h * hROT;
[m... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | reduceKD.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/reduceKD.m | 3,536 | utf_8 | 64e442e25ac5fe30874c408a16385e0f | function [q,e,c]=reduceKD(p,varargin)
% KD-tree based density reduction method of Ihler et al, 2004.
%
costType = 'kld'; maxCost = .01;
costs = ones(1,2*getNpts(p)); % cost-matrix in terms of # components
for i=1:length(varargin)
if (isa(varargin{i},'char')), costType = varargin{i}; end;
if (isa(varargin{i... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | ksizeHall.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/ksizeHall.m | 3,035 | utf_8 | c5314c96ba500c8f5f1a37c6a859eaac | function h = ksizeHall(npd)
%
% Find kernel size according to "plug-in" method of
% Hall, Marron, Sheather, Jones (91)
%
%
% Copyright (C) 2003 Alexander Ihler; distributable under GPL -- see README.txt
x = getPoints(npd);
[N1,N2] = size(x);
sig = std(x,0,2); % estimate sigma (standard... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | reduceKD2.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/reduceKD2.m | 2,015 | utf_8 | dd67a8f3df4e3759d5d0878fc7bee42e | function q=reduceKD(p,maxCost,costType)
if (nargin < 3) costType = 1; end; % "max" cost
if (nargin < 2) maxCost = round(getNpts(p)/10); end;
bw = getBW(p,1); out = kde(mean(p),3*covar(p)); outW = .999; N = getNpts(p);
ind = [1]; done = []; eC=zeros(1,2*N); eC(1) = cost(p,1,bw,out,outW,costType);
done = ind; ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | ksizeCalcUseful.m | .m | ContextualMultiCameraTracker-master/libs/@kde/private/ksizeCalcUseful.m | 2,075 | utf_8 | cf1830a47aafdbd7969c237259045a20 | function ksizeCalcUseful
%
% ksizeCalcUseful
% -- find some useful numbers for the various kernels
%
%
% Kernel size calculations for Rule of Thumb, Maximal Smoothing Principle
% Assume that true density f is Gaussian (or whatever)
% and find h_\infty = BW minimizing AMISE (Asymp. Mean Squared Err)
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | cheby0.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sdpt3/Examples/cheby0.m | 2,576 | utf_8 | a31e95ee5e80694cd1c3f2ceb594d369 | %%**********************************************************
%% cheby0:
%%
%% minimize || p(d) ||_infty
%% p = polynomial of degree <= m such that p(0) = 1.
%%
%% Here d = n-vector
%%----------------------------------------------------------
%% [blk,Avec,C,b,X0,y0,Z0,objval,p] = cheby0(d,m,solve);
%%
%% d ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | make.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/make.m | 18,843 | utf_8 | fe8ce82cbeffb34ed474dc781d6a440a | function make( varargin )
%
% Determine the base path
%
odir = cd;
try
base = dbstack( '-completenames' );
base = base(1);
base = base.file;
catch
base = dbstack;
base = base(1);
base = base.name;
end
base = fileparts( base );
fclose all;
close all;
%
% Check the force an... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | cantilever_beam_plot.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/cvxbook/Ch04_cvx_opt_probs/cantilever_beam_plot.m | 1,050 | utf_8 | e8c8c9e1b601e4102f96e0436649d132 | % Plots a cantilever beam as a 3D figure.
% This is a helper function for the optimal cantilever beam example.
%
% Inputs:
% values: an array of heights and widths of each segment
% [h1 h2 ... hN w1 w2 ... wN]
%
% Almir Mutapcic 01/25/06
function cantilever_beam_plot(values)
N = length(values)/2;
for k ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | simple_step.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/circuit_design/simple_step.m | 248 | utf_8 | ce47b4b6778bdb78f1098a2f2dc06205 | % Computes the step response of a linear system
function X = simple_step(A,B,DT,N)
n = size(A,1);
Ad = expm( full( A * DT ) );
Bd = ( Ad - eye(n) ) * B;
Bd = A \ Bd;
X = zeros(n,N);
for k = 2 : N,
X(:,k) = Ad*X(:,k-1)+Bd;
end
|
github | santhosh-kumar/ContextualMultiCameraTracker-master | spectral_fact.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/filter_design/spectral_fact.m | 1,292 | utf_8 | 014eebfa2dfbbd038c1383ff2ef97b0e | % Spectral factorization using Kolmogorov 1939 approach.
% (code follows pp. 232-233, Signal Analysis, by A. Papoulis)
%
% Computes the minimum-phase impulse response which satisfies
% given auto-correlation.
%
% Input:
% r: top-half of the auto-correlation coefficients
% starts from 0th element to end of the au... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | polar_plot_ant.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/antenna_array_design/polar_plot_ant.m | 1,149 | utf_8 | 34a08a3bc75c474d61e01ea58b16e54e | % Plot a polar plot of an antenna array sensitivity
% with lines denoting the target direction and beamwidth.
% This is a helper function used in the broadband antenna examples.
%
% Inputs:
% X: an array of abs(y(theta)) where y is the antenna array pattern
% theta0: target direction
% bw: total beamw... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | spectral_fact.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/antenna_array_design/spectral_fact.m | 1,385 | utf_8 | 570e7ae2165d19abd477494c52e609f8 | % Spectral factorization using Kolmogorov 1939 approach
% (code follows pp. 232-233, Signal Analysis, by A. Papoulis)
%
% Computes the minimum-phase impulse response which satisfies
% given auto-correlation.
%
% Input:
% r: top-half of the auto-correlation coefficients
% starts from 0th element to end of the aut... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | plotgraph.m | .m | ContextualMultiCameraTracker-master/libs/cvx/examples/graph_laplacian/plotgraph.m | 3,172 | utf_8 | a46b1d761798c492e96a5b9504aea9aa | function plotgraph(A,xy,weights)
% Plots a graph with each edge width proportional to its weight.
%
% Edges with positive weights are drawn in blue; negative weights in red.
%
% Input parameters:
% A --- incidence matrix of the graph (size is n x m)
% (n is the number of nodes and m is the number of e... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | disp.m | .m | ContextualMultiCameraTracker-master/libs/cvx/lib/@cvxprob/disp.m | 5,342 | utf_8 | c7d4f1798c1fe6afff368b38f460f115 | function disp( prob, prefix )
if nargin < 2, prefix = ''; end
global cvx___
p = cvx___.problems( index( prob ) );
if isempty( p.variables ),
nvars = 0;
else
nvars = length( fieldnames( p.variables ) );
end
if isempty( p.duals ),
nduls = 0;
else
nduls = length( fieldnames( p.duals ) );
end
neqns = ( l... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | apply.m | .m | ContextualMultiCameraTracker-master/libs/cvx/lib/@cvxtuple/apply.m | 744 | utf_8 | f2da301079043e6e789dc429ca7d060b | function y = apply( func, x )
y = do_apply( func, x.value_ );
function y = do_apply( func, x )
global cvx___
switch class( x ),
case 'struct',
y = cell2struct( do_apply( func, struct2cell( x ) ), fieldnames( x ), 1 );
case 'cell',
if cvx___.hcellfun,
y = cellfun( func, x, 'UniformOu... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | testall.m | .m | ContextualMultiCameraTracker-master/libs/cvx/lib/@cvxtuple/testall.m | 674 | utf_8 | 21ffb9bdf2b39de834fadf2074c36667 | function y = testall( func, x )
y = do_test( func, x.value_ );
function y = do_test( func, x )
global cvx___
switch class( x ),
case 'struct',
y = do_test( func, struct2cell( x ) );
case 'cell',
if cvx___.hcellfun,
y = all( cellfun( func, x ) );
else
y = true;
... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | disp.m | .m | ContextualMultiCameraTracker-master/libs/cvx/lib/@cvxtuple/disp.m | 1,260 | utf_8 | 1eef0644949e0e9257e06d734492404e | function disp( x, prefix )
if nargin < 2,
prefix = '';
end
disp( [ prefix, 'cvx tuple object: ' ] );
prefix = [ prefix, ' ' ];
do_disp( x.value_, {}, prefix, prefix, '' );
function do_disp( x, f, fprefix, prefix, suffix )
switch class( x ),
case 'struct',
do_disp( struct2cell(x), fieldnames(x), fpref... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | sparsify.m | .m | ContextualMultiCameraTracker-master/libs/cvx/lib/@cvx/sparsify.m | 4,218 | utf_8 | 1165e2dcf37b47b46df8a43e2aa05b8b | function x = sparsify( x, mode )
global cvx___
error( nargchk( 2, 2, nargin ) );
persistent remap
%
% Check mode argument
%
if ~ischar( mode ) || size( mode, 1 ) ~= 1,
error( 'Second arugment must be a string.' );
end
isobj = strcmp( mode, 'objective' );
pr = cvx___.problems( end );
touch( pr.se... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | rotlorentz.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/rotlorentz.m | 1,734 | utf_8 | 2360f679ed280039c549592a3c993aff | % c = rotlorentz(c,K)
% Rotates vectors from Qcone to Rcone or from Rcone into Qcone.
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi
function c = rotlorentz(c,K)
%
% This file is part of SeDuMi 1.1 by Imre Polik and Oleksandr Romanko
% Copyright (C) 2005 McMaster University, Ham... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | PopK.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/PopK.m | 2,058 | utf_8 | f5d78e3b27636285dfc03b5da8fcbc93 | % [y, ddotx, Dx, xTy] = PopK(d,x,K,lpq)
% POPK Implements the quadratic operator for symmetric cones K.
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi
function [y, ddotx, Dx, xTy] = PopK(d,x,K,lpq)
%
% This file is part of SeDuMi 1.1 by Imre Polik and Olek... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | updtransfo.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/updtransfo.m | 4,683 | utf_8 | ad0b99f49325c720a6fcf6a3e16c7aba | % [d,vfrm] = updtransfo(x,z,w, dIN,K)
% UPDTRANSFO Updated the Nesterov-Todd transformation using a
% numerically stable method.
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi
function [d,vfrm] = updtransfo(x,z,w, dIN,K)
%
% This file is par... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | symbcholden.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/symbcholden.m | 2,555 | utf_8 | ba6fe026b0102d1fd909b6903c62aa1f | % Lden = symbcholden(L,dense,DAt)
% SYMBCHOLDEN Creates Lden.{LAD, perm,dz, sign, first}
%
% ******************** INTERNAL FUNCTION OF SEDUMI ********************
%
% See also sedumi, dpr1fact
function Lden = symbcholden(L,dense,DAt)
%
% This file is part of SeDuMi ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | eyeK.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/eyeK.m | 1,838 | utf_8 | ffa2c00f778c6f9b0074de0a1c512ede | % eyeK Identity w.r.t. symmetric cone.
% x = eyeK(K) produces the identity solution w.r.t. the symmetric cone,
% that is described by the structure K. This is the vector for which
% eigK(x) is the all-1 vector.
%
% See also eigK.
function x = eyeK(K) %#ok
% This file is part of SeDuMi 1.1 by Imre... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | sparfwslv.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/sparfwslv.m | 2,276 | utf_8 | b0e876743c52edb4ceb0cee125503411 | % SPARFWSLV Solves block sparse upper-triangular system.
% y = sparfwslv(L,b) yields the same result as
% y = L.L\b(L.perm,:)
% However, SPARFWSLV is faster than the built-in operator "\",
% because it uses dense linear algebra and loop-unrolling on
% supernodes.
%
% For sparse b, one... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | fwdpr1.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/fwdpr1.m | 1,885 | utf_8 | 11f29cfa3a4db03ceb164e006e122f73 | % y = fwdpr1(Lden, b)
% FWDPR1 Solves "PROD_k L(pk,betak) * y = b", where
% where L(p,beta) = eye(n) + tril(p*beta',-1).
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi, dpr1fact, bwdpr1
function y = fwdpr1(Lden, b) %#ok
... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | sortnnz.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/sortnnz.m | 2,009 | utf_8 | ff6d6feeafc76605dc5849101a512fe7 | % perm = sortnnz(At,Ajc1,Ajc2)
% SORTNNZ Sorts columns in At
% in increasing order of nnzs; only the nnzs between Ajc1 and Ajc2
% are considered for each column. If Ajc1 or Ajc2 is empty, we use
% the start or end of the columns in At.
%
% *******************... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | loopPcg.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/loopPcg.m | 6,270 | utf_8 | c663b50c5b75f46e8f1ed2b8234e7b12 | % [y,k, DAy] = loopPcg(L,Lden,At,dense,d, DAt,K, b,p,ssqrNew,cgpars, restol)
%
% LOOPPCG Solve y from AP(d)A' * y = b
% using PCG-method and Cholesky L as conditioner.
% If L is sufficiently accurate, then only 1 CG-step is needed.
% It assumes that the previous step was p, with
% ssqrNew = bOld'*inv(L*THETA*L')*... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | finsymbden.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/finsymbden.m | 2,139 | utf_8 | b7db26946dcb4437abb6c2c42346ef80 | % Lden = finsymbden(LAD,perm,dz,firstq)
% FINSYMBDEN Updates perm and dz by inserting the
% last Lorentz trace columns (last columns of LAD). It creates the fields
% Lden.sign - +1 for "normal" columns, -1 for Lorentz trace columns
% Lden.first - First pivot column that will a... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | getDAtm.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/getDAtm.m | 2,007 | utf_8 | 34c7a3a2c33ccc2675038ad7141d5ac1 | % DAt = getDAtm(A,Ablkjc,dense,DAtdenq,d,K)
% GETDATM Computes d[k]'*Aj[k] for each lorentz block k and constraint j.
%
% ******************** INTERNAL FUNCTION OF SEDUMI ********************
%
% See also sedumi, getada2.
function DAt = getDAtm(A,Ablkjc,dense,DAtdenq,d,K)... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | findblks.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/findblks.m | 2,048 | utf_8 | c7e00aa66b2573d3c707dba4034bd751 | % Ablk = findblks(At,Ablkjc,blk0,blk1,blkstart)
% FINDBLKS Find nonzero blocks
% in A, with subscripts per column bounded bij Ablkjc([blk0,blk1]),
% block partitioned by blkstart.
% If blk0 < 1 (blk1 > size(Ablkjc,2)) then start (stop) searching at column
% start (end) of A.
%
% ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | invcholfac.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/invcholfac.m | 1,864 | utf_8 | a765bc06810ddda5c15851aaf08e1d72 | % y = invcholfac(u,K, perm)
% INVCHOLFAC Computes y(perm,perm) = u' * u, with u upper triangular.
%
% ******************** INTERNAL FUNCTION OF SEDUMI ********************
%
% See also sedumi, getada3
function y = invcholfac(u,K, perm) %#ok
%
% This file is ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | qframeit.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/qframeit.m | 1,773 | utf_8 | d09af1c0a97090bae278b9ab98bae212 | % x = qframeit(lab,frmq,K)
%
% *********************** INTERNAL FUNCTION OF SEDUMI *******************
%
% See also sedumi
% This file is part of SeDuMi 1.1 by Imre Polik and Oleksandr Romanko
% Copyright (C) 2005 McMaster University, Hamilton, CANADA (since 1.1)
%
% Copyright (C) 2001 Jos F. Sturm (up to ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | incorder.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/incorder.m | 2,199 | utf_8 | 39bd1057030e6bc62a42e7c457c7e550 | % [perm, dz] = incorder(At [,Ajc1,ifirst])
% INCORDER
% perm sorts the columns of At greedily, by iteratively picking
% the 1st unprocessed column with the least number of nonzero
% subscripts THAT ARE NOT YET COVERED (hence incremental) by
% the previously processed columns.
% dz... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | qreshape.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/qreshape.m | 2,009 | utf_8 | a4f5fe91301be1c2c80790d32b364cc6 | % y = qreshape(x,flag, K)
% QRESHAPE Reshuffles entries associated with Lorentz blocks.
% If flag = 0 then y = [x1 for each block; x2 for each block]
% If flag = 1 then y = [x block 1; x block 2; etc], etc
% Thus, x = qreshape(qreshape(x,0,K),1,K).
%
% *********... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | dpr1fact.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/dpr1fact.m | 2,135 | utf_8 | 6e1515974b7f69a55818f487066a01f9 | % [Lden,L.d] = dpr1fact(x, d, Lsym, smult, maxu)
% DPR1FACT Factor d[iag] p[lus] r[ank] 1:
% [Lden,L.d] = dpr1fact(x, d, Lsym, smult, maxu)
% Computes fi and d such that
% diag(d_IN) + x*diag(smult)*x' =
%(PI_{i=1}^n L(p_OUT^i,beta_i)) * diag(d_OUT) * (PI_{i=1}^n L(p_OUT^... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | iswnbr.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/iswnbr.m | 4,458 | utf_8 | bd35b69263e14666e8c4b7031e8dedd0 | % [delta,h,alpha] = iswnbr(vSQR,thetaSQR)
% ISWNBR Checks feasibility w.r.t. wide region/neighborhood of Sturm-Zhang.
% vTAR:= (1-alpha)*max(h,v) projection v onto theta-central region
% delta = (sqrt(n)/theta) * norm(vTAR - v) / norm(v)
%
% ********** INTERNAL FUNCTION OF SEDUMI *... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | fwblkslv.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/fwblkslv.m | 2,009 | utf_8 | 6b1bc0e352178a2797aaa4b855e18975 | % FWBLKSLV Solves block sparse upper-triangular system.
% y = fwblkslv(L,b) yields the same result as
% y = L.L\b(L.perm,:)
% However, FWBLKSLV is faster than the built-in operator "\",
% because it uses dense linear algebra and loop-unrolling on
% supernodes.
%
% Typical use, with X ... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | trydif.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/trydif.m | 2,561 | utf_8 | 188705faedb79d0ad34ec9dcdf8d1f2c | % [t,wr,w] = trydif(t,wrIN,wIN, x,z, pars,K)
% TRYDIF Tries feasibility of differentiated step length w.r.t.
% wide region and its neighborhood.
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi, stepdif
function [t,wr,w] = trydif(t,wrIN,wIN, x,z, pars,K)
%
% This... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | asmDxq.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/asmDxq.m | 2,803 | utf_8 | 8d99cd2fd94ebd77f97312468887a518 | % y = asmDxq(d, x, K [, ddotx])
% ASMDXQ Assemble y = D(d)x for x in Lorentz part of K.
% [y,t] = AasmDxq(d, x, K [, ddotx]) then y[k]+t(k)*d[k] = D(dk)xk.
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi
function [y,t] = asmDxq(d, x, K, ddot... |
github | santhosh-kumar/ContextualMultiCameraTracker-master | symfctmex.m | .m | ContextualMultiCameraTracker-master/libs/cvx/sedumi/symfctmex.m | 2,041 | utf_8 | 82d47b253b1c0f69e20894a97bc19d5e | % [L,perm,xsuper,split,tmpsiz] = symfctmex(X, perm, cachsz)
% Computes sparse symbolic factor L, updated permutation PERM,
% super-node partition XSUPER, and a splitting of supernodes
% (SPLIT) to optimize use of the computer cache (assuming
% CACHSZ*1024 byte available). TMPSIZ is the amount of floating
... |
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