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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_roc.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/plotop/vl_roc.m | 6,848 | utf_8 | 3d7ed746da2d3f389ad56c8e36f006d7 | function [tpr,tnr,info] = vl_roc(labels, scores, varargin)
% VL_ROC Compute ROC curve
% [TP,TN] = VL_ROC(LABELS, SCORES) computes the receiver operating
% characteristic (ROC curve). LABELS are the ground thruth labels (+1
% or -1) and SCORE is the scores assigned to them by a classifier
% (higher scores correspond... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_click.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/plotop/vl_click.m | 2,661 | utf_8 | 6982e869cf80da57fdf68f5ebcd05a86 | function P = vl_click(N,varargin) ;
% VL_CLICK Click a point
% P=VL_CLICK() let the user click a point in the current figure and
% returns its coordinates in P. P is a two dimensiona vectors where
% P(1) is the point X-coordinate and P(2) the point Y-coordinate. The
% user can abort the operation by pressing any k... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_ubcread.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/sift/vl_ubcread.m | 3,015 | utf_8 | e8ddd3ecd87e76b6c738ba153fef050f | function [f,d] = vl_ubcread(file, varargin)
% SIFTREAD Read Lowe's SIFT implementation data files
% [F,D] = VL_UBCREAD(FILE) reads the frames F and the descriptors D
% from FILE in UBC (Lowe's original implementation of SIFT) format
% and returns F and D as defined by VL_SIFT().
%
% VL_UBCREAD(FILE, 'FORMAT', '... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_plotsiftdescriptor.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/sift/vl_plotsiftdescriptor.m | 4,348 | utf_8 | b9a98b0c298fa249fb5fcd1314762b88 | function h=vl_plotsiftdescriptor(d,f,varargin)
% VL_PLOTSIFTDESCRIPTOR Plot SIFT descriptor
% VL_PLOTSIFTDESCRIPTOR(D) plots the SIFT descriptors D, stored as
% columns of the matrix D. D has the same format used by VL_SIFT().
%
% VL_PLOTSIFTDESCRIPTOR(D,F) plots the SIFT descriptors warped to
% the SIFT fram... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_twister.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_twister.m | 1,166 | utf_8 | 1e18a0b343ffe164ec9c941e18575c05 | function vl_test_twister
% VL_TEST_TWISTER
% test seed by scalar
rand('twister',1) ; a = rand ;
vl_twister('state',1) ; b = vl_twister ;
check(a,b,'twister: seed by scalar + VL_TWISTER()') ;
% read state
rand('twister') ; a = rand('twister') ;
vl_twister('state') ; b = vl_twister('state') ;
check(a,b,'twister: read s... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_imintegral.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_imintegral.m | 1,257 | utf_8 | d5ad8d073e99ff451cc1b692da99ec6d | function vl_test_imintegral
I = ones(5,6);
correct = [1 2 3 4 5 6;
2 4 6 8 10 12;
3 6 9 12 15 18;
4 8 12 16 20 24;
5 10 15 20 25 30;];
if ~all(all(slow_imintegral(I) == correct))
fpri... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_sift.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_sift.m | 1,849 | utf_8 | cfae71614a40aebf645eb42102ca53f3 | function vl_test_sift
% VL_TEST_SIFT Test VL_SIFT implementation(s)
I = vl_test_pattern(101);
% run various instances of the code
[a0,b0] = vl_sift(single(I),'verbose','peaktresh',0,'levels',4) ;
[a1,b1] = cmd_sift(I,'--first-octave=0 --peak-tresh=0 --levels=4') ;
[a2,b2] = cmd_sift(I,'--first-octave=0',1) ;
[a3,... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_binsum.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_binsum.m | 1,030 | utf_8 | c69da861d697e8228e243a385f5ba545 | function vl_test_binsum
% VL_TEST_BINSUM Test VL_BINSUM function
testh({[0 0], 1, 2}, [0 1] ) ;
testh({[1 7], -1, 1}, [0 7] ) ;
testh({[1 7], -1, [1 2 2 2 2 2 2 2]}, [0 0] ) ;
testh({eye(3), [1 1 1], [1 2 3], 1 }, 2*eye(3)) ;
testh({eye(3), [1 1 1]', [1 2 3]', 2 }, 2*eye... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_imsmooth.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_imsmooth.m | 1,566 | utf_8 | 27ae6791e4ca852539a031b78ae7a00b | function vl_test_imsmooth
I = im2double(imread('data/spots.jpg')) ;
I = max(min(imresize(I,2),1),0) ;
I = single(I) ;
global fign ;
fign = 1 ;
step = 1 ;
ker = 'gaussian' ;
testmany(I,'triangular',1) ;
testmany(I,'triangular',2) ;
testmany(I,'gaussian',1) ;
testmany(I,'gaussian',2) ;
function testmany(I,ker,step)... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_hikmeans.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_hikmeans.m | 2,037 | utf_8 | f57532e5de667fbe2f6cb9c714f20457 | function vl_test_hikmeans
% VL_TEST_HIKMEANS Test VL_HIKMEANS function
K = 2;
nleaves = 2;
data = uint8(rand(2,100)*255);
[tree,A] = vl_hikmeans(data,K,nleaves,'verbose','verbose');
%keyboard;
K = 3 ;
nleaves = 100 ;
data = uint8(rand(2,1000) * 255) ;
datat = uint8(rand(2,10000)* 255) ;
[... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_homkmap.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_homkmap.m | 1,493 | utf_8 | a78c933efd15a4279e2724ba4441ad76 | function vl_test_homkmap
x = 2.^(-12:.1:0) ;
L = .3 ;
n = 4 ;
V = vl_homkmap(x, n, L, 'kchi2') ;
V_ = featureMap('chi2', n, L, x, 1) ;
V
V_
figure(1) ; clf ;
subplot(1,2,1) ;
semilogx(x,V_','-') ; hold on ;
semilogy(x,V','--') ;
subplot(1,2,2);
plot(x,V_','-') ; hold on ;
plot(x,V','--') ;
function psi = feat... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_aibhist.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_aibhist.m | 2,263 | utf_8 | d46c6fa557ab0d00e465eaedd060add9 | % VL_TEST_AIBHIST
function vl_test_aibhist
D = 4 ;
K = 20 ;
randn('state',0) ;
rand('state',0) ;
X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ;
X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ;
X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ;
C = 1:K*K ;
Pcx = zeros(3,K*K) ;
f1 = quantize(X1,D,K) ;
f2 = quantize(X2,D,K) ;... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | vl_test_ikmeans.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/toolbox/test/vl_test_ikmeans.m | 1,552 | utf_8 | 1d5747a991a0d81ed4f7a2c90cd2a213 | function vl_test_ikmeans
% VL_TEST_IKMEANS Test VL_IKMEANS function
fprintf('test_ikmeans: Testing VL_IKMEANS and IKMEANSPUSH\n')
% -----------------------------------------------------------------------
fprintf('test_ikmeans: Testing Lloyd algorithm\n')
K = 3 ;
data = uint8(rand(2,1000) * 255) ;
datat = ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | phow_caltech101.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/apps/phow_caltech101.m | 11,269 | utf_8 | 91ef403a7a3865b32e7a5673350fec49 | function phow_caltech101
% PHOW_CALTECH101 Image classification in the Caltech-101 dataset
% This program demonstrates how to use VLFeat to construct an image
% classifier on the Caltech-101 data. The classifier uses PHOW
% features (dense SIFT), spatial histograms of visual words, and a
% Chi2 SVM. To speedup ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | sift_mosaic.m | .m | MultiviewAppearanceTracker-master/lib/vlfeat-0.9.14/apps/sift_mosaic.m | 4,621 | utf_8 | 8fa3ad91b401b8f2400fb65944c79712 | function mosaic = sift_mosaic(im1, im2)
% SIFT_MOSAIC Demonstrates matching two images using SIFT and RANSAC
%
% SIFT_MOSAIC demonstrates matching two images based on SIFT
% features and RANSAC and computing their mosaic.
%
% SIFT_MOSAIC by itself runs the algorithm on two standard test
% images. Use SIFT_MOSAI... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | phasecong2.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/phasecong2.m | 23,162 | utf_8 | 4ddd1ae0a78576bcc859e76d6b483b33 | % PHASECONG2 - Computes edge and corner phase congruency in an image.
%
% This function calculates the PC_2 measure of phase congruency.
% This function supersedes PHASECONG
%
% There are potentially many arguments, here is the full usage:
%
% [M m or ft pc EO] = phasecong2(im, nscale, norient, minWaveLength... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | lowpassfilter.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/lowpassfilter.m | 2,448 | utf_8 | 1bdb6b9b70b06af9d2bc12b6b877da54 | % LOWPASSFILTER - Constructs a low-pass butterworth filter.
%
% usage: f = lowpassfilter(sze, cutoff, n)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutoff is the cutoff frequency of the filter 0 - 0.5
% n is the order of the f... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | hysthresh.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/hysthresh.m | 2,218 | utf_8 | 1083374237be0a6bad69e6afd431e1c0 | % HYSTHRESH - Hysteresis thresholding
%
% Usage: bw = hysthresh(im, T1, T2)
%
% Arguments:
% im - image to be thresholded (assumed to be non-negative)
% T1 - upper threshold value
% T2 - lower threshold value
% (T1 and T2 can be entered in any order, the larger o... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | dispfeat.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/dispfeat.m | 6,082 | utf_8 | 1baad565a14949d330f8fe298e5a0322 | % DISPFEAT - Displays feature types as detected by PHASECONG.
%
% This function provides a visualisation of the feature types as detected
% by PHASECONG.
%
% Usage: im = dispfeat(ft, edgeim, 'l')
%
% Arguments: ft - An image providing the local weighted mean
% phase angle at every point in t... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | edgelink.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/edgelink.m | 12,668 | utf_8 | 82e1c8da57382b35f5eda4dedc9b2c5c | % EDGELINK - Link edge points in an image into lists
%
% Usage: [edgelist edgeim] = edgelink(im, minlength, location)
%
% Arguments: im - Binary edge image, it is assumed that edges
% have been thinned.
% minlength - Optional minimum edge length of interest, defaults
% ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | phasecong.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/phasecong.m | 16,644 | utf_8 | 693c5ec683ef5ce8c816379185261bf7 | % PHASECONG - Computes phase congruency on an image.
%
% Usage: [pc or ft] = phasecong(im)
%
% This function calculates the PC_2 measure of phase congruency.
% For maximum speed the input image should be square and have a
% size that is a power of 2, but the code will operate on images
% of arbitrary size.
%
%
% R... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | nonmaxsup.m | .m | MultiviewAppearanceTracker-master/lib/VTD_CODE_V7.0/PHASE/nonmaxsup.m | 6,600 | utf_8 | f72536506a96132d3571ac8ec2148caf | % NONMAXSUP - Non-maxima suppression
%
% Usage:
% [im,location] = nonmaxsup(inimage, orient, radius);
%
% Function for performing non-maxima suppression on an image using an
% orientation image. It is assumed that the orientation image gives
% feature normal orientation angles in degrees (0-180).
%
% Input:
... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | SetupCameraNetwork.m | .m | MultiviewAppearanceTracker-master/src/SetupCameraNetwork.m | 3,617 | utf_8 | 269ba44f525e183b3daea48c80f24b69 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function sets up the camera network
%
% Input --
% void
% Output --
% @cameraNetwork - Structure containing the camera networks
% @frameRangeForAnalysis - frame range
%
% Author -- Sa... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | TRACE_LOG.m | .m | MultiviewAppearanceTracker-master/src/TRACE_LOG.m | 445 | utf_8 | abf85c76a5a52dec4b65251f7ceafd47 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Logs info
%
% Author -- Santhoshkumar Sunderrajan
% Website -- http://www.uweb.ucsb.edu/~santhoshkumar/
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function TRACE_LOG( message )
global FID %#ok<TLEV>... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | CheckRegionOfInterest.m | .m | MultiviewAppearanceTracker-master/src/@Target/CheckRegionOfInterest.m | 1,170 | utf_8 | d321c083f1831a03dc1ec403f46058b7 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function checks region of interest for the given frameNumber.
% Give in an image with 2 rectangles in the image, get out all pixels.
% This is done for getting the inner and outer masks used in the
% subsequent training proce... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | DisplayParticles.m | .m | MultiviewAppearanceTracker-master/src/@ParticleFilter/DisplayParticles.m | 1,861 | utf_8 | be078449a6fd9c33e03bdf57305173d0 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Display Particles
%
% Input --
% @obj - object of type Particle Filter
% @imageFrame - image frame
%
% Output --
% void
%
% Author -- Santhoshkumar Sunderrajan( santhoshkumar@umail.ucsb.edu )
%
%... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | PredictParticle.m | .m | MultiviewAppearanceTracker-master/src/@ParticleFilter/PredictParticle.m | 898 | utf_8 | d4022fd2cbd7807a8f2d1a3b0d851c34 | % predict a single particle
function particle = PredictParticle( varianceX,...
varianceY,...
varianceScaleX,...
varianceScaleY,...
particle )
... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | transition.m | .m | MultiviewAppearanceTracker-master/src/@ParticleFilter/transition.m | 1,787 | utf_8 | 3e2da1366c9b736378de98211b8ec5c0 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Transition the statematrix according to constant velocity mdoel.
%
% Input --
% @obj - object of type ParticleFilter
%
% Output --
% @transitionStateMatrix - transitioned state matrix
%
% Author -- Santhoshkumar Su... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | Initialize.m | .m | MultiviewAppearanceTracker-master/src/@ParticleFilter/Initialize.m | 2,125 | utf_8 | 7569876d6c588fa50b8032777c041e1e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Initialize particle filter
%
% Input --
% @obj - object of type ParticleFilter
% @centerX - x center of the object
% @centerY - y center of the object
% @scaleX - x scale
% @scaleY - y scale
%... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | Predict.m | .m | MultiviewAppearanceTracker-master/src/@ParticleFilter/Predict.m | 2,422 | utf_8 | f9f73fcbe2f4203f5d1908ab5c0d2f48 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Predict the particle state with brownian motion
%
% Input --
% @obj - object of type ParticleFilter
% @varianceX - x position variance
% @varianceY - y position variance
% @varianceScale... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | Update.m | .m | MultiviewAppearanceTracker-master/src/@ParticleFilter/Update.m | 726 | utf_8 | 5132abb9eff7db6f41e07f672d6f6bc9 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Update the particle weights
%
% Input --
% @obj - object of type ParticleFilter
% @posteriorStateMatrix - posterior state matrix
%
% Output --
% @obj - object of type ParticleFilter... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | ExtractFeatures.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/ExtractFeatures.m | 3,306 | utf_8 | 6a88113d8fdcf58398ab6552981ca28e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function extracts features on the given image and stores it
% in the appropriate variable
%
% Input --
% @obj - - Ensemble Classifier Object
% @inputImage - Input Image
% @phase - TRAIN or TES... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | GetBestPerformingWeakClassifiers.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/GetBestPerformingWeakClassifiers.m | 1,353 | utf_8 | 0201275186c0a7f2d38441fb39decd98 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function gets the best performing classifier to be shared
% with the other views
%
% Input --
% @obj - - Ensemble Classifier Object
%
% Output --
% @weakClassifierList - Weak C... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | PrepareForegroundAndBackgroundMasks.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/PrepareForegroundAndBackgroundMasks.m | 4,450 | utf_8 | 4fa059c97465ad0fab010464e619e4ee | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function is for preparing foreground and background masks that are
% are used in training.
%
% Input --
% @obj - object of type EnsembleClassifier
% @frameImage - image of the current frame... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | Initialize.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/Initialize.m | 2,062 | utf_8 | 52195c1813985a785b37f973b5cbcd56 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function initializes Ensemble Classifier.
%
% Input --
% @obj - - Ensemble Classifier Object
% @initializationImageFrame - Input Image
% @objectRectangle - object rectangle
... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | Test.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/Test.m | 3,705 | utf_8 | 35813495ab765122f0e9e644972338fb | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function tests the Ensemble Classifier on the given test image
%
% Input --
% @obj - - Ensemble Classifier Object
% @frameImage - Input Image
% @previousTargetRectangle ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | GetNegativeSamplesForCorrelatedObjects.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/GetNegativeSamplesForCorrelatedObjects.m | 1,704 | utf_8 | 4c34475c8a073303da27e93479835aca | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function extracts negative examples that are consistent
% across views
%
% Input --
% @obj - Ensemble Classifier Object
% @weakClassifierList - weak classifier list
%
% Output --
% ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | Update.m | .m | MultiviewAppearanceTracker-master/src/@EnsembleClassifier/Update.m | 2,953 | utf_8 | 7130a35bc538000c141e8b11620c2c6f | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function updates the Ensemble Classifier on the given training
% image
%
% Input --
% @obj - - Ensemble Classifier Object
% @frameImage - Input Image
% @objectRectang... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | xml2struct.m | .m | MultiviewAppearanceTracker-master/src/@CameraModel/xml2struct.m | 6,960 | utf_8 | d679d0d3ed2307d44c3986192af212d7 | function [ s ] = xml2struct( obj, file )
%Convert xml file into a MATLAB structure
% [ s ] = xml2struct( file )
%
% A file containing:
% <XMLname attrib1="Some value">
% <Element>Some text</Element>
% <DifferentElement attrib2="2">Some more text</Element>
% <DifferentElement attrib3="2" attrib4="1">Even m... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | InitializeTracker.m | .m | MultiviewAppearanceTracker-master/src/@Camera/InitializeTracker.m | 2,499 | utf_8 | c67f884378c21afdcff886156c7fa5ee | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function initializes target manually.
%
% Input --
% @obj - camera object.
% @localFeatureType - Feature Type for appearance modeling
% @globalFeatureType - Feature Type for global appearance modeling
% Ou... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | VisualizeTrackerOutput.m | .m | MultiviewAppearanceTracker-master/src/@Camera/VisualizeTrackerOutput.m | 1,157 | utf_8 | 1d65906c64440a33c8f9a551b9613a3b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Visualizes the tracker output
%
% Input --
% @obj - Camera object
% @networkStruct - Information about the network structure
%
% Output --
% void
%
% Author -- Santhoshkumar Sunderrajan( santhos... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | ExtractColorHistogramFeature.m | .m | MultiviewAppearanceTracker-master/src/@Features/ExtractColorHistogramFeature.m | 1,750 | utf_8 | e219c2bd9f06bd5f45ca1d67aee833a0 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Features::ExtractColorHistogramFeature
% Extracts Multi-dimensional color histogram.
% Input --
% obj - Feature Object
% imageBlock - Image Block
% isVectorized - Is Vectorized Image
% numbe... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | ExtractHOGFeatures.m | .m | MultiviewAppearanceTracker-master/src/@Features/ExtractHOGFeatures.m | 3,324 | utf_8 | 1165cd27d2ffae9fa51bf384b788ac05 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Features::ExtractHOGFeatures
%
% Extracts HOG Feature
%
% Input --
% obj - Feature Object
% inputImage - Input Image
% roiMask ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | GetMultiDimensionalColorHistogram.m | .m | MultiviewAppearanceTracker-master/src/@Features/GetMultiDimensionalColorHistogram.m | 2,917 | utf_8 | 5ef6e56ce289b6ef260a98244101c8f7 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%This function sets the parameters of the DKF based on the intial state
%
% Input --
% @I - Input color image ( can be a vectorized i... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | ExtractRawColorFeatures.m | .m | MultiviewAppearanceTracker-master/src/@Features/ExtractRawColorFeatures.m | 1,595 | utf_8 | 4238cee15f4e3e260fc3ce943a540c16 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Features::ExtractRawColorFeatures
%
% Extracts raw color pixel features Feature
%
% Input --
% obj - Feature Object
% inputImage - Input Image
% r... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | CollectContextInformation.m | .m | MultiviewAppearanceTracker-master/src/@Filter/CollectContextInformation.m | 1,130 | utf_8 | b9da376370bb58675cf3895abfe1b295 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function collects contextual information from the given camera
% view
%
% Input --
% @cameraNetwork
% @cameraIndex
% @targetIndex
%
% Output --
% @zj - current measurement on the ground plane
... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | PerformFiltering.m | .m | MultiviewAppearanceTracker-master/src/@Filter/PerformFiltering.m | 1,539 | utf_8 | 24976b5a58b7405d90ff2e8cbcbcfeec | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function performs filtering.
%
% Input --
% @cameraNetwork - Structure containing the camera networks
%
% Output --
% @cameraNetwork - Structure containing the camera networks
%
% Author -- Santhos... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | CollectMeasurments.m | .m | MultiviewAppearanceTracker-master/src/@Filter/CollectMeasurments.m | 1,570 | utf_8 | 1c63b3afd7dfaa58f54b5502d2beb6f7 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function collects measurements from different cameras for the
% specified object.
%
% Input --
% @cameraNetwork - Structure containing the camera networks.
% @cameraIndex - camera index
% @targetIndex... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | CollectTrainingSamples.m | .m | MultiviewAppearanceTracker-master/src/@AppearanceModel/CollectTrainingSamples.m | 1,864 | utf_8 | 8128ce125035643608560d35f90464ce | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function learns both local and global object appearance.
%
% Input --
% @cameraNetwork - Structure containing the camera networks.
% @cameraIndex - camera index
% @targetIndex - target index
% Output --
%... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | LearnGlobalAppearanceModel.m | .m | MultiviewAppearanceTracker-master/src/@AppearanceModel/LearnGlobalAppearanceModel.m | 1,850 | utf_8 | ff896d92293e53e0e7397ffe11861e68 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function learns both global object appearance.
%
% Input --
% @cameraNetwork - Structure containing the camera networks.
% @frameIndex - frame index (number)
% Output --
% @cameraNetwork - Structure contain... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | LearnObjectsAppearancesAcrossDifferentViews.m | .m | MultiviewAppearanceTracker-master/src/@AppearanceModel/LearnObjectsAppearancesAcrossDifferentViews.m | 1,143 | utf_8 | 174954e06b8b3757e5f7f117139e2877 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function learns both local and global object appearance.
%
% Input --
% @cameraNetwork - Structure containing the camera networks.
% @frameIndex - frame index (number)
% Output --
% @cameraNetwork - Structu... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | SampleFromGenerativeSubspace.m | .m | MultiviewAppearanceTracker-master/src/@AppearanceModel/SampleFromGenerativeSubspace.m | 2,441 | utf_8 | b08b837618b5b9903ae089ce43dec00e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function updates the Ensemble Classifier on the given training
% image
%
% Input --
% @trainingFeatures - Training Features
% @trainingLabels - Training Labels
% @otherViewTrainingSamples ... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | LearnLocalAppearanceModel.m | .m | MultiviewAppearanceTracker-master/src/@AppearanceModel/LearnLocalAppearanceModel.m | 762 | utf_8 | ec3880c3198fd051169b40cfd4a68614 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function learns the local appearance model for different objects
%
% Input --
% @cameraNetwork - Structure containing the camera networks.
% @frameIndex - frame index (number)
% Output --
% @cameraNetwork -... |
github | santhosh-kumar/MultiviewAppearanceTracker-master | SampleFromGenerativeSubspace (santhosh-mbp's conflicted copy 2014-05-26).m | .m | MultiviewAppearanceTracker-master/src/@AppearanceModel/SampleFromGenerativeSubspace (santhosh-mbp's conflicted copy 2014-05-26).m | 3,223 | utf_8 | d0ea40138ad67c165ae605c5a8fc9297 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function updates the Ensemble Classifier on the given training
% image
%
% Input --
% @trainingFeatures - Training Features
% @trainingLabels - Training Labels
% @otherViewTrainingSamples ... |
github | shriman/SemProject-master | convolve2.m | .m | SemProject-master/convolve2/convolve2.m | 5,525 | utf_8 | ce0d819240c38ae2f582dcbc50f71bb9 | function y = convolve2(x, m, shape, tol)
%CONVOLVE2 Two dimensional convolution.
% Y = CONVOLVE2(X, M) performs the 2-D convolution of matrices X and
% M. If [mx,nx] = size(X) and [mm,nm] = size(M), then size(Y) =
% [mx+mm-1,nx+nm-1]. Values near the boundaries of the output array are
% calculated as if X was s... |
github | shriman/SemProject-master | exindex.m | .m | SemProject-master/convolve2/exindex.m | 9,835 | utf_8 | abe5b0ee2b5b9191c2913af2070fd137 | function arr = exindex(arr, varargin)
%EXINDEX extended array indexing
% ARROUT = EXINDEX(ARRIN, S1, S2, ...) indexes a virtual array made by
% extending ARRIN with zeros in all directions, using subscripts S1, S2
% etc.
%
% ARROUT = EXINDEX(ARRIN, S1, R1, S2, R2, ...) extends ARRIN using rule
% R1 on ... |
github | mjlong123123/RemoteCamera-master | echo_diagnostic.m | .m | RemoteCamera-master/jni/speex/libspeex/echo_diagnostic.m | 2,076 | utf_8 | 8d5e7563976fbd9bd2eda26711f7d8dc | % Attempts to diagnose AEC problems from recorded samples
%
% out = echo_diagnostic(rec_file, play_file, out_file, tail_length)
%
% Computes the full matrix inversion to cancel echo from the
% recording 'rec_file' using the far end signal 'play_file' using
% a filter length of 'tail_length'. The output is saved to 'o... |
github | BSAM/BSAM1.2-master | interface2d.m | .m | BSAM1.2-master/PROBLEM/MATLAB/interface2d.m | 4,129 | utf_8 | b579a7f01764a6a7a253d3cc6cf8aa76 | function[] = cntrplot2d(s0,nn,var,toggle0,toggle1,toggle2)
%
% s0 is the string indicating the appropriate PROBLEM directory, eg, 'CH'
% nn is the frame number to be printed
% var is the variable number
% toggle0 = 0 for adaptive mesh
% toggle0 = 1 for uniform mesh
% toggle1 = 0 for no output
% toggle1 = 1 for jpg outp... |
github | BSAM/BSAM1.2-master | meshinterface2d.m | .m | BSAM1.2-master/PROBLEM/MATLAB/meshinterface2d.m | 4,436 | utf_8 | fc465b439502d22b345b8d383094aaeb | function[] = meshcntrplot2d(s0,nn,var,toggle0,toggle1,toggle2)
%
% s0 is the string indicating the appropriate PROBLEM directory, eg, 'CH'
% nn is the frame number to be printed
% var is the variable number
% toggle0 = 0 for adaptive mesh
% toggle0 = 1 for uniform mesh
% toggle1 = 0 for no output
% toggle1 = 1 for jpg ... |
github | BSAM/BSAM1.2-master | interface3d.m | .m | BSAM1.2-master/PROBLEM/MATLAB/interface3d.m | 5,572 | utf_8 | d5dfc84e126ac32abf23c387c0e469d6 | function[] = surfplot3d(s0,nn,var,toggle1,toggle2)
%
% s0 is the string indicating the appropriate PROBLEM directory, eg, 'CH'
% nn is the iteration number to print
% var is the variable number
% Set toggle1 = 0 for no output
% Set toggle1 = 1 for jpg output
% Set toggle1 = 2 for eps output
% Set toggle2 = 0 to print o... |
github | ojwoodford/ibr_toolbox-master | truncquad_edges.m | .m | ibr_toolbox-master/ojw/truncquad_edges.m | 1,030 | utf_8 | 4af153ae70344b1c928af948e8f6329f | %TRUNCQUAD_EDGES Compute truncated quadratic pairwise texture costs
%
% edge_costs = truncquad_edges(I, modes, EI, thresh)
%
% Computes the truncated quadratic cost of each combination of pairs of
% modes in each edge, based on the minimum distance to a pair of pixels in
% the corresponding library.
%
% IN:
... |
github | ojwoodford/ibr_toolbox-master | truncquad_modes.m | .m | ibr_toolbox-master/ojw/truncquad_modes.m | 1,300 | utf_8 | 7722f349eb550773a02d1f2a78ac59d5 | %TRUNCQUAD_MODES Compute colour modes for a truncated quadratic kernel
%
% [modes depth energy inliers] = truncquad_modes(I, thresh[, use_variance[, search_width]])
%
% Computes the colour modes for each set of input vectors, using the
% truncated quadratic kernel.
%
% IN:
% I - CxLxM array of L input colo... |
github | ojwoodford/ibr_toolbox-master | P_interp.m | .m | ibr_toolbox-master/ojw/P_interp.m | 1,770 | utf_8 | 921030bc998d5ef446f99ae9c4c55b8e | function P = P_interp(first, last, frames)
%P_INTERP Linear interpolation between 2 projection matrices
%
% P = P_interp(first, last, frames)
%
% Creates a series off projection matrices interpolated from two projection
% matrices.
%
%IN:
% first - 3x4 The first projection matrix in the series, and the fi... |
github | ojwoodford/ibr_toolbox-master | ojw_segpln.m | .m | ibr_toolbox-master/ojw/ojw_segpln.m | 5,727 | utf_8 | 44d8d4908d827efa9fdc0f11904bdf79 | function [D info] = ojw_segpln(images, P, disps, R, options)
%OJW_SEGPLN Generate piecewise-planar disparity proposals for stereo
%
% [D info] = ojw_segpln(images, P, disps, R, options)
%
% Generates a set of disparity map proposals for the first input image.
%
%IN:
% images - 1xN cell array of input image... |
github | ojwoodford/ibr_toolbox-master | compile.m | .m | ibr_toolbox-master/ojw/compile.m | 15,029 | utf_8 | 65c29de5564837102abc6a673f2d385c | %COMPILE Mex compilation helper function
%
% Examples:
% compile func1 func2 ... -option1 -option2 ...
%
% This function can be used to (re)compile a number of mex functions, but
% is also a helper function enabling inline compilation.
function varargout = compile(varargin)
% There are two types of call:
%... |
github | ojwoodford/ibr_toolbox-master | ibr_fuse_depths.m | .m | ibr_toolbox-master/ojw/ibr_fuse_depths.m | 15,344 | utf_8 | b06c6fa36f7bce29358c6cfafb28f2d1 | function [N info energy V] = ibr_fuse_depths(D1, D2, vals)
%IBR_FUSE_DEPTHS Fuse two disparity images using QPBO
%
% [N info energy V] = ibr_fuse_depths(D0, D1, vals)
%
% Given two disparity maps and input data (image sequence, projection
% matrices and configuration parameters) this function will fuse the two... |
github | ojwoodford/ibr_toolbox-master | find_interactions.m | .m | ibr_toolbox-master/ojw/find_interactions.m | 870 | utf_8 | c44185f1b638419a9783168ebd02e6a6 | %FIND_INTERACTIONS Given ordered 3d points, find occlusions pairs
%
% P = find_interactions(V)
%
% Given a set of 3d image coordinates (pixel coordinates plus depth),
% ordered such that the x coordinates are monotonically increasing, as are
% the y coordinates within each block of identical x coordinates, fin... |
github | ojwoodford/ibr_toolbox-master | ibr_gen_cliques.m | .m | ibr_toolbox-master/ojw/ibr_gen_cliques.m | 863 | utf_8 | 3c41190e82e3c553a1d84e05030c90f0 | %IBR_GEN_CLIQUES Generate graph cliques given visibilities
%
% [U P PI T TI] = ibr_gen_cliques(IA, VA, V, Kocc, method)
%
% Generates graph cliques for the algorithm described in Woodford etal.'s
% BMVC 2007 paper:
% "On New View Synthesis Using Multiview Stereo".
%
% IN:
% IA - 1xN cell array of input ... |
github | ojwoodford/ibr_toolbox-master | sc.m | .m | ibr_toolbox-master/ojw/sc.m | 32,939 | utf_8 | 34495279b3a0ff89df9db7631adf5d5e | function I = sc(I, varargin)
%SC Display/output truecolor images with a range of colormaps
%
% Examples:
% sc(image)
% sc(..., limits)
% sc(..., colormap)
% out = sc(...)
% sc
%
% Generates a truecolor RGB image based on the input values in 'image' and
% any maximum and minimum limits specified, u... |
github | ojwoodford/ibr_toolbox-master | vgg_progressbar.m | .m | ibr_toolbox-master/vgg/vgg_progressbar.m | 4,301 | utf_8 | d4541c2ac2b1b469245005ae628b0d3c | function retval = vgg_progressbar(tag, proportion, min_update_interval)
%VGG_PROGRESSBAR Simple progress bar implementation
%
% retval = vgg_progressbar(tag, proportion[, min_update_interval])
%
% Starts, updates and closes a progress bar according to the proportion of
% time left.
%
% IN:
% tag - String ... |
github | ojwoodford/ibr_toolbox-master | vgg_interp2.m | .m | ibr_toolbox-master/vgg/vgg_interp2.m | 1,346 | utf_8 | 692121537aeeffdb06012e0e7bdc12dc | %VGG_INTERP2 Fast 2d interpolation for images
%
% V = vgg_interp2(A, X, Y)
% V = vgg_interp2(A, X, Y, interp_mode)
% V = vgg_interp2(A, X, Y, interp_mode, oobv)
%
% 2d interpolation on a regular grid - similar to matlab's interp2() but
% with much less overhead, and supports multiple channels and types. Note
%... |
github | ojwoodford/ibr_toolbox-master | vgg_trw_bp.m | .m | ibr_toolbox-master/vgg/vgg_trw_bp.m | 2,530 | utf_8 | 733c1a3d64df60079f5ca1a87d60c7c5 | %VGG_TRW_BP Multi-label MRF energy minimization using TRW-S & LBP
%
% [L energy lower_bound] = vgg_trw_bp(UE, PI, PE, [options])
%
% Uses the message passing algorithms TRW-S or LBP to solve an MRF energy
% minimization problem with binary or multiple labels.
%
% This function uses mexified C++ code written b... |
github | ojwoodford/ibr_toolbox-master | vgg_qpbo.m | .m | ibr_toolbox-master/vgg/vgg_qpbo.m | 4,498 | utf_8 | 2235034c3e89ecb1aa54cdfa6e7379dd | %VGG_QPBO Binary MRF energy minimization on non-submodular graphs
%
% [L stats] = vgg_qpbo(UE, PI, PE, [TI, TE], [options])
%
% Uses the Quadratic Pseudo-Boolean Optimization (QPBO - an extension of
% graph cuts that solves the "roof duality" problem, allowing graphs with
% submodular edges to be solved) to so... |
github | ojwoodford/ibr_toolbox-master | vgg_segment_ms.m | .m | ibr_toolbox-master/vgg/vgg_segment_ms.m | 1,618 | utf_8 | 7720c82fa1381cb8ef7746ff1914dd78 | %VGG_SEGMENT_MS Mean shift image segmentation
%
% S = vgg_segment_ms(A, h_s, h_r, min_sz[, W])
%
% Segmentation of an image using mean shift.
%
% Uses EDISON code by Chris Christoudias and Bogdan Georgescu, downloaded
% from http://www.caip.rutgers.edu/riul/research/code/EDISON/index.html,
% and based on th... |
github | ojwoodford/ibr_toolbox-master | vgg_segment_gb.m | .m | ibr_toolbox-master/vgg/vgg_segment_gb.m | 1,304 | utf_8 | c770886681ca25380e78baf579e64d85 | %VGG_SEGMENT_GB Graph-based image segmentation
%
% S = vgg_segment_gb(A, sigma, K, min_sz[, compress])
%
% Segmentation of an image using the graph-based method described in:
% "Efficient Graph-Based Image Segmentation.", Pedro F. Felzenszwalb and
% Daniel P. Huttenlocher. International Journal of Computer... |
github | sakov/gridgen-c-master | viewgrid.m | .m | gridgen-c-master/gridgen/examples/viewgrid.m | 3,941 | utf_8 | 63ebcbc9b6f7c16b11ebecbc20009e39 | function viewgrid(prm, v)
% VIEWGRID Visualises grids generated by `gridgen'.
% Usage:
% viewgrid('<gridgen prm file>') -- display grid only
% viewgrid('<gridgen prm file>', 'v') -- display grid and image on one
% chart, vertically one under another
% viewgrid('<gr... |
github | sakov/gridgen-c-master | vg.m | .m | gridgen-c-master/gridgen/examples/vg.m | 1,183 | utf_8 | 2a8d994426377e38886f9bed5cd0fd13 | function vg(fname)
[nx, ny, x, y] = fload(fname);
xmin = min(x);
xmax = max(x);
ymin = min(y);
ymax = max(y);
xdiff = xmax - xmin;
ydiff = ymax - ymin;
diff = max([xdiff ydiff]) / 20.0;
xmin = xmin - diff;
xmax = xmax + diff;
ymin = ymin - diff;
ymax = ymax + diff;
figure;
title(fname);
... |
github | keskarnitish/OBA-master | OBA.m | .m | OBA-master/OBA.m | 10,431 | utf_8 | 744a5bb89e5eacffe6519d51c14abf0f | function X = OBA(fun,lambda,options)
% OBA : A Second-Order Method for Convex L1-Regularized Optimization with Active Set Prediction
% Minimization algorithm intended for composite convex functions and
% specifically for high-dimensional problems.
% Usage: X = OBA(fun,lambda,[options])
% returns the approximate mi... |
github | zhhoper/ADMM_stereo-master | reconstructDepthMap.m | .m | ADMM_stereo-master/reconstructDepthMap.m | 1,354 | utf_8 | 410db83d9178c88a60ccc3b34795c98c | function [Z, C, D] = reconstructDepthMap(S,imgsize)
addpath('../simulate');
rows = imgsize(1);
cols = imgsize(2);
pixels = rows*cols;
num_equ = (rows-1)*cols + (cols-1)*rows;
C = zeros(num_equ, pixels);
D = zeros(num_equ, 1);
% x direction
pos = 0;
[Sx, Sy] = getGradientField(S,imgsize);
for j=1:cols
for i=1:rows-... |
github | zhhoper/ADMM_stereo-master | reconstructDepthMap_adapted_mask.m | .m | ADMM_stereo-master/reconstructDepthMap_adapted_mask.m | 1,908 | utf_8 | 7d5fb74240a566a5d4c5fa68dcaf82fb | function [Z, C, D] = reconstructDepthMap_adapted_mask(S,imgsize, mask)
% construct depth map using gradients with given mask
addpath('simulate');
[xEdge, yEdge] = findEdges(mask);
validX = logical(mask.*(~xEdge));
validY = logical(mask.*(~yEdge));
validX = validX(1:end-1, :);
validY = validY(:, 1:end-1);
indX = valid... |
github | zhhoper/ADMM_stereo-master | ADMM_opt.m | .m | ADMM_stereo-master/ADMM_opt.m | 6,781 | utf_8 | f55be39c6844f68c5a9c1ae93ad57f46 | function result = ADMM_opt(var)
% var contains all the variables we need to solve this problem
% var.M contains the observations
% var.W contains the mask
% var.X, var.l3, var.lam, var.Z, var.img_row, var_img_col
max_ite = 600;
threshold = 0.001;
count = 0;
%var_old = var;
diff = inf;
[obj, obj1, obj2, obj3] = object... |
github | zhhoper/ADMM_stereo-master | reconstructDepthMap_adapted.m | .m | ADMM_stereo-master/reconstructDepthMap_adapted.m | 1,387 | utf_8 | ce6b028c2b9596f97c380c1b2cb11f51 | function [Z, C, D] = reconstructDepthMap_adapted(S, imgsize)
addpath('simulate');
rows = imgsize(1);
cols = imgsize(2);
pixels = rows*cols;
[Sx, Sy] = getGradientField(S,imgsize);
Sx = Sx(1:end-1,:);
Sy = Sy(:, 1:end-1);
% x direction
[indx, indy] = meshgrid(1:rows-1, 1:cols);
C1 = zeros((rows-1)*cols, pixels);
indx... |
github | zhhoper/ADMM_stereo-master | showImages.m | .m | ADMM_stereo-master/functions/showImages.m | 561 | utf_8 | 5935be1e561cd91dd7eb7221ec050034 | % Saves the measurements to separate images
function [fig] = showImages(varargin)
M = varargin{1};
s = varargin{2};
if nargin == 3
vis = varargin{3};
else
vis = 'on';
end
cols = ceil(sqrt(size(M,1)));
rows = ceil(size(M,1)/ cols);
fig = figure('Name','Input', 'visible',... |
github | zhhoper/ADMM_stereo-master | plotStats.m | .m | ADMM_stereo-master/functions/plotStats.m | 1,719 | utf_8 | a49cbccb36233850b64a9d57a33a7f95 | %% Plots stats
function [ fig] = plotStats(varargin)
stats = varargin{1};
nameX = varargin{2};
nameY = varargin{3};
usePoints = 'median';
fitFunction = 'linearinterp';
if nargin > 4
usePoints = varargin{4};
fitFunction = varargin{5};
end
fig = figure;
hold on;
stats.Scenario = nominal(categorical(stats.Scena... |
github | zhhoper/ADMM_stereo-master | SigmaxDefaultParams.m | .m | ADMM_stereo-master/solvers/SigmaxDefaultParams.m | 2,561 | utf_8 | 63be9308280cc39e3c8a8af3912323e9 | %% Default params for Sigmax
function params = SigmaxDefaultParams(imgsize,mode)
params = struct();
params.mustImproveAfterIters = 20;
params.errDecayThreshold = 0.002;
params.spectralErrThreshold = 1e-5;
params.dataErrThreshold = 1e-5;
params.initWith = 'M';
... |
github | zhhoper/ADMM_stereo-master | PlainSolver.m | .m | ADMM_stereo-master/solvers/PlainSolver.m | 1,783 | utf_8 | 992404e3049e2fa2ebc22135810781ba | %% This is a very primitive solver for comparison.
%% It always returns closest plain as a surface.
%%
%% params: imgsize
%% result: M,L,S,R,Z, breakReason
function [M,L,S,R,Z, breakReason] = PlainSolver(MIn, params)
knownInds = MIn > 0;
if size(knownInds(knownInds==0),1) > 0
fprintf('Compl... |
github | zhhoper/ADMM_stereo-master | SigmaxSolver.m | .m | ADMM_stereo-master/solvers/SigmaxSolver.m | 16,511 | utf_8 | b42f9ae4b5e3030eab8f98c7b634e37f | %% Completes the matrix using the start values stored in the Solver
%%
%% params: maxErrIn, spectralErrThreshold, boundSpecErr, GT
%%
%% result: iterations, ANew,
%% specErr, distErr
%% breakReason,
%% LNew, RNew, ZNew, ANew
function [result] = SigmaxSolver(M, para... |
github | zhhoper/ADMM_stereo-master | damped_wiberg_new.m | .m | ADMM_stereo-master/external/damped_wiberg_new.m | 8,358 | utf_8 | 6320443cf09f30a98b4963f08ade13ed | function [U, V, err, iter, err_log, lambda_log] = damped_wiberg_new(Y, H, r, Vini, tol, max_iter, disp_level)
% The damped Wiberg algorithm for low-rank matrix factorization Y -> U V'
%
% [U, V] = damped_wiberg(Y, H, r) factorizes the data matrix Y (say m x n)
% into the product of U (m x r) and V (n x r). Note that r ... |
github | zhhoper/ADMM_stereo-master | PSNR.m | .m | ADMM_stereo-master/external/TNNR_code/TNNR_code/TNNR-admm/PSNR.m | 500 | utf_8 | 28df45d9404dcbfa235005e85470727d | % written by debingzhang
% if you have any questions, please fell free to contact
% debingzhangchina@gmail.com
% version 1.0, 2012.11.16
function [ psnr ] = PSNR( Xfull,Xrecover,missing )
Xrecover = max(0,Xrecover);
Xrecover = min(255,Xrecover);
[m,n,dim] = size(Xrecover);
MSE = 0;
for i =1 : di... |
github | zhhoper/ADMM_stereo-master | admmAXB.m | .m | ADMM_stereo-master/external/TNNR_code/TNNR_code/TNNR-admm/admmAXB.m | 1,072 | utf_8 | 5a87ce628469593b7e584f5594ad5cad | % written by debingzhang
% if you have any questions, please fell free to contact
% debingzhangchina@gmail.com
% version 1.0, 2012.11.16
function [ X,iterations] = admmAXB( A,B,X,M,known,rho)
% my_admm
% solve minimize ||X||_*-trace(A*X*B')
MAX_ITER = 200;
[m,n] = size(M);
%r = size(A,1);
U = X;
V = zeros(m,n... |
github | zhhoper/ADMM_stereo-master | admm_pic.m | .m | ADMM_stereo-master/external/TNNR_code/TNNR_code/TNNR-admm/admm_pic.m | 2,549 | utf_8 | d763341418859e0660370c86cd9fe85d |
% written by debingzhang
% if you have any questions, please fell free to contact
% debingzhangchina@gmail.com
% version 1.0, 2012.11.16
function [ret fullpsnr] = admm_pic(image_name,matrix_pic,matrix_mask,to_create_eps_pic,lower_R,upper_R)
%% nothing needs to be changed below
Xfull = matrix_pic;
mask = matrix_mask... |
github | zhhoper/ADMM_stereo-master | my_apgl.m | .m | ADMM_stereo-master/external/TNNR_code/TNNR_code/TNNR-apgl/my_apgl.m | 1,586 | utf_8 | 546668102b9814e0a8fafd114a903fbe | function [XX,iterations] = my_apgl(A,B,X,M,known,eps,lambda)%,Xfull,inmissing)
% min g(x)+h(x) g(x) = -trace(AXB)+\lambda*||X_\Omega - M_\Omega||_F^2, h(x) = ||X||_*
if (~exist('eps','var'))
eps = 0.1;
end
if (~exist('lambda','var'))
lambda = 0.00000000000000000001;
end
AB =... |
github | zhhoper/ADMM_stereo-master | g2sTikhonovStd.m | .m | ADMM_stereo-master/external/grad2SurfV1-0/grad2Surf/g2sTikhonovStd.m | 5,374 | utf_8 | 30ffeb79ca3eb60bc19675ca944bb98b | function [ Z, lamOpt, RC, Theta ] = g2sTikhonovStd( Zx, Zy, x, y, N, noLambdas, Z0 )
%
% Purpose : Computes the Global Least Squares reconstruction of a surface
% from its gradient field with Tikhonov regularization in Standard form,
% while estimating the optimal regularization parameter by means of the
% L-Curv... |
github | zhhoper/ADMM_stereo-master | figure2eps.m | .m | ADMM_stereo-master/external/DOPBoxV1-8/SupportFns/figure2eps.m | 7,698 | utf_8 | d41f8c3ab703fea8f87f1f5b919bc580 | function figure2eps(H,fileName, maxNrPatches, BitMapRenderer, forcePainter )
%
% Purpose : This function saves a figure to EPS. It enables the use of
% different renderers for surfces, patches and other graphical objects.
%
% Axes, text etc are rendered using vector graphics.
%
% The total number of surface patches an... |
github | meskatjahan/PCA-master | pca_1.m | .m | PCA-master/pca_1.m | 2,027 | utf_8 | 00e32944181f2db0dded01665fa5f5cb |
function [r]= pca_1(a)
%takes a matrix as a input
% Detailed explanation goes here
% a=[1 2 3; 4 5 6; 7 8 9];
a = [269.8 38.9 50.5
272.4 39.5 50.0
270.0 38.9 50.5
272.0 39.3 50.2
269.8 38.9 50.5
269.8 38.9 50.5
268.2 38.6 50.2
268.2 38.6 50.8
267.0 38.2 51.1
267.8 38.4 51.0
273.6 39.6 50.0
271.2 39.1 50.4
26... |
github | iwbailey/thermomech-master | creep_arrh.m | .m | thermomech-master/src/fortran/ifiles/creep_arrh.m | 4,430 | utf_8 | b01c39641f3e3cb8572dd77567ea038b | function [faultCrp, faultE] = creep_arrh( nx, nz, fLength, fWidth, actEnergy, ...
zBD, stressBD, tempBD, vPl, R_g, dTdz)
% Setup the creep parameters for the arrhenius verion of creep
% Distance from BD transition to use for perturbation
dzPerturb = 1.25;
% Width of border re... |
github | iwbailey/thermomech-master | creep_bz1996.m | .m | thermomech-master/src/fortran/ifiles/creep_bz1996.m | 2,834 | utf_8 | bab9ce9f98c69706e33cd94b7e56cfba | function [crp, actEn] = creep_bz1996( nx, nz, fLength, fWidth, zDB, tauratioz, ...
vPl, fs, dSigmaEff_dz )
dx = fLength/nx; % Slip cell length in km
dz = fWidth/nz; % Slip cell depth in km
xDB = fWidth - zDB;
% Creep parameter at zDB. Makes Vcreep = vPl at zDB if tau = fs*Seff at... |
github | iwbailey/thermomech-master | tempfromheat.m | .m | thermomech-master/matlab/heat/tempfromheat.m | 723 | utf_8 | 7ae0af79a6cf25e43939d38b5c06621a | function temp = tempfromheat( heatRate, cellArea, t1, t2, tNow, faultWidth, ...
diffusivity, density, specHeat )
%
% temp = tempfromheat( heatRate, cellArea, t1, t2, tNow, faultWidth, diffusivity )
%
temp = inst_temp(heatRate, cellArea, faultWidth, density, specHeat)*...
integ_tempdecay( t1, t2, tNow, f... |
github | iwbailey/thermomech-master | integ_tempdecay.m | .m | thermomech-master/matlab/heat/integ_tempdecay.m | 1,747 | utf_8 | 751cf2967070ea945a272657e6d62aaa | function result = integ_tempdecay( tSlipStart, tSlipEnd, tNow, faultWidth, diffusivity )
%INTEG_TEMPDECAY
%
% result = integ_tempdecay( tSlipStart, tSlipEnd, tNow, faultWidth, diffusivity )
% Check what time to return heat for
% Error tolerance
EPS = 1e-12;
result = zeros(size(tNow));
isNZ = tNow>tSlipStart;
if( ~a... |
github | iwbailey/thermomech-master | strikeslipstrain.m | .m | thermomech-master/matlab/fault/strikeslipstrain.m | 1,674 | utf_8 | 2e26343b9f0cbb2046a60c0db66b0868 | function strain = strikeslipstrain( halfwidth, halfdepth, zStrain, xStress, zStress )
%STRIKESLIPSTRAIN calc shear strain for point source due to unit slip
%
% strain = strikeslipstrain( xw2, xd2, x3, y1, y3 )
%
% Chinnery solution for stress due to strike slip on a vertical, rectangular
% fault patch (followi... |
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