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Misc. modules/ cont. pt2

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This commit is contained in:
luz.paz
2018-02-13 11:28:11 -05:00
parent 252e871a8b
commit d05714995c
75 changed files with 195 additions and 195 deletions
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modules/video/src/bgfg_KNN.cpp
+2 -2
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@@ -281,7 +281,7 @@ protected:
////////////////////////
int history;
//alpha=1/history - speed of update - if the time interval you want to average over is T
//set alpha=1/history. It is also usefull at start to make T slowly increase
//set alpha=1/history. It is also useful at start to make T slowly increase
//from 1 until the desired T
float fTb;
//Tb - threshold on the squared distance from the sample used to decide if it is well described
@@ -289,7 +289,7 @@ protected:
//and that is Tb=2*2*10*10 =400; where we take typical pixel level sigma=10
/////////////////////////
//less important parameters - things you might change but be carefull
//less important parameters - things you might change but be careful
////////////////////////
int nN;//totlal number of samples
int nkNN;//number on NN for detcting background - default K=[0.1*nN]
modules/video/src/bgfg_gaussmix2.cpp
+7 -7
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@@ -42,7 +42,7 @@
/*//Implementation of the Gaussian mixture model background subtraction from:
//
//"Improved adaptive Gausian mixture model for background subtraction"
//"Improved adaptive Gaussian mixture model for background subtraction"
//Z.Zivkovic
//International Conference Pattern Recognition, UK, August, 2004
//http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf
@@ -91,7 +91,7 @@ namespace cv
/*
Interface of Gaussian mixture algorithm from:
"Improved adaptive Gausian mixture model for background subtraction"
"Improved adaptive Gaussian mixture model for background subtraction"
Z.Zivkovic
International Conference Pattern Recognition, UK, August, 2004
http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf
@@ -351,7 +351,7 @@ protected:
// and that is varThreshold=4*4=16; Corresponds to Tb in the paper.
/////////////////////////
// less important parameters - things you might change but be carefull
// less important parameters - things you might change but be careful
////////////////////////
float backgroundRatio;
// corresponds to fTB=1-cf from the paper
@@ -407,7 +407,7 @@ struct GaussBGStatModel2Params
int nHeight;
int nND;//number of data dimensions (image channels)
bool bPostFiltering;//defult 1 - do postfiltering - will make shadow detection results also give value 255
bool bPostFiltering;//default 1 - do postfiltering - will make shadow detection results also give value 255
double minArea; // for postfiltering
bool bInit;//default 1, faster updates at start
@@ -417,7 +417,7 @@ struct GaussBGStatModel2Params
////////////////////////
float fAlphaT;
//alpha - speed of update - if the time interval you want to average over is T
//set alpha=1/T. It is also usefull at start to make T slowly increase
//set alpha=1/T. It is also useful at start to make T slowly increase
//from 1 until the desired T
float fTb;
//Tb - threshold on the squared Mahalan. dist. to decide if it is well described
@@ -426,7 +426,7 @@ struct GaussBGStatModel2Params
//and that is Tb=4*4=16;
/////////////////////////
//less important parameters - things you might change but be carefull
//less important parameters - things you might change but be careful
////////////////////////
float fTg;
//Tg - threshold on the squared Mahalan. dist. to decide
@@ -471,7 +471,7 @@ struct GMM
};
// shadow detection performed per pixel
// should work for rgb data, could be usefull for gray scale and depth data as well
// should work for rgb data, could be useful for gray scale and depth data as well
// See: Prati,Mikic,Trivedi,Cucchiara,"Detecting Moving Shadows...",IEEE PAMI,2003.
CV_INLINE bool
detectShadowGMM(const float* data, int nchannels, int nmodes,
modules/video/src/lkpyramid.cpp
+2 -2
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@@ -876,7 +876,7 @@ namespace
std::vector<UMat> prevPyr; prevPyr.resize(maxLevel + 1);
std::vector<UMat> nextPyr; nextPyr.resize(maxLevel + 1);
// allocate buffers with aligned pitch to be able to use cl_khr_image2d_from_buffer extention
// allocate buffers with aligned pitch to be able to use cl_khr_image2d_from_buffer extension
// This is the required pitch alignment in pixels
int pitchAlign = (int)ocl::Device::getDefault().imagePitchAlignment();
if (pitchAlign>0)
@@ -886,7 +886,7 @@ namespace
for (int level = 1; level <= maxLevel; ++level)
{
int cols,rows;
// allocate buffers with aligned pitch to be able to use image on buffer extention
// allocate buffers with aligned pitch to be able to use image on buffer extension
cols = (prevPyr[level - 1].cols+1)/2;
rows = (prevPyr[level - 1].rows+1)/2;
prevPyr[level] = UMat(rows,(cols+pitchAlign-1)&(-pitchAlign),prevPyr[level-1].type()).colRange(0,cols);