使用matlab對行人視頻進行檢測的代碼的分析

function F = hogcalculator(img,cellpw,cellph, nblockw, nblockh,nthet,overlap, isglobalinterpolate, issigned, normmethod)
% HOGCALCULATOR calculate R-HOG feature vector of an input image using the
% procedure presented in Dalal and Triggs's paper in CVPR 2005.Note that at the end of this code, there are some demonstration code，please remove in your work.
% F = hogcalculator(img, cellpw, cellph, nblockw, nblockh,nthet, overlap, isglobalinterpolate, issigned, normmethod)
%IMG:
%IMG is the input image.
%CELLPW, CELLPH:
%CELLPW and CELLPH are cell's pixel width and height respectively.
%NBLOCKW, NBLCOKH:
%NBLOCKW and NBLCOKH are block size counted by cells number in x and y directions respectively.
%NTHET, ISSIGNED:
%NTHET is the number of the bins of the histogram of oriented gradient. The histogram of oriented gradient ranges from 0 to pi in
%'unsigned' condition while to 2*pi in 'signed' condition, which can be specified through setting the value of the variable ISSIGNED by the string 'unsigned' or 'signed'.
%OVERLAP:
%OVERLAP is the overlap proportion of two neighboring block(兩個相鄰塊的重疊比例).
%ISGLOBALINTERPOLATE:
%ISGLOBALINTERPOLATE specifies whether the trilinear interpolation(三線性插入)is done in a single global 3d histogram of the whole detecting window by the 
%string 'globalinterpolate' or in each local 3d histogram corresponding to respective blocks by the string 'localinterpolate' which is in strict accordance with the 
%procedure proposed in Dalal's paper. Interpolating in the whole detecting window requires the block's sliding step(滑動步長)to be an integral multiple of cell's width and height 
%because the histogram is fixing before interpolate. In fact here the so called 'globalinterpolation' is a notation(符號，註釋)given by myself. at first the spatial interpolation is done 
%without any relevant to block's slide position, but when I was doing calculation %while OVERLAP is 0.75, something occurred 
%NORMMETHOD：
%NORMMETHOD is the block histogram normalized method which can be set as one of the following strings:
%'none', which means non-normalization;
%'l1', which means L1-norm normalization;
%'l2', which means L2-norm normalization;
%'l1sqrt', which means L1-sqrt-norm normalization;
%'l2hys', which means L2-hys-norm normalization.
% F：
%F is a row vector storing the final histogram of all of the blocks one by one in a top-left to bottom-right image scan manner, the cells histogram are stored in the
%same manner in each block's section of F.Note that CELLPW*NBLOCKW and CELLPH*NBLOCKH should be equal to IMG's width and height respectively.
%Here is a demonstration, which all of parameters are set as the best value mentioned in Dalal's paper when the window detected is 128*64 size(128 rows, 64 columns):
%F = hogcalculator(window, 8, 8, 2, 2, 9, 0.5,'localinterpolate', 'unsigned', 'l2hys');
%Also the function can be called like:F = hogcalculator(window);
%the other parameters are all set by using the above-mentioned "dalal's
%best value" as default.
if nargin < 2
%set default parameters value.
cellpw = 8;
cellph = 8; 
nblockw = 2;
nblockh = 2;
nthet = 9; 
overlap = 0.5;
isglobalinterpolate = 'globalinterpolate';
issigned = 'unsigned';
normmethod = 'l2hys';
else 
if nargin < 10
error('Input parameters are not enough.');
end
end
% check parameters's validity(有效性；正確性；正確).
img=imread('G:\生活\有趣的圖片\鬥地主.jpg');
[M, N, K] = size(img);
if mod(M,cellph*nblockh) ~= 0 
error('IMG''s height should be an integral multiple of CELLPH*NBLOCKH.');
end
if mod(N,cellpw*nblockw) ~= 0
error('IMG''s width should be an integral multiple of CELLPW*NBLOCKW.');
end
if mod((1-overlap)*cellpw*nblockw, cellpw) ~= 0 ||mod((1-overlap)*cellph*nblockh, cellph) ~= 0
str1 = 'Incorrect OVERLAP or ISGLOBALINTERPOLATE parameter';
str2 = ', slide step should be an intergral multiple of cell size';
error([str1, str2]);
end
% set the standard deviation(偏差；背離；誤差)of gaussian spatial weight window.
delta = cellpw*nblockw * 0.5;
% calculate gradient scale matrix
hx = [-1,0,1];
hy = -hx';
gradscalx = imfilter(double(img),hx);
gradscaly = imfilter(double(img),hy);
if K > 1
gradscalx = max(max(gradscalx(:,:,1),gradscalx(:,:,2)), gradscalx(:,:,3));
gradscaly = max(max(gradscaly(:,:,1),gradscaly(:,:,2)), gradscaly(:,:,3));
end
gradscal = sqrt(double(gradscalx.*gradscalx + gradscaly.*gradscaly));
% calculate gradient orientation matrix.
% plus small number for avoiding dividing zero.
gradscalxplus = gradscalx+ones(size(gradscalx))*0.0001;
gradorient = zeros(M,N);
% unsigned situation: orientation region is 0 to pi.
if strcmp(issigned, 'unsigned') == 1 
gradorient =atan(gradscaly./gradscalxplus) + pi/2;
or = 1;
else
% signed situation: orientation region is 0 to 2*pi.
if strcmp(issigned, 'signed') == 1
idx = find(gradscalx >= 0 & gradscaly >= 0);
gradorient(idx) = atan(gradscaly(idx)./gradscalxplus(idx));
idx = find(gradscalx < 0);
gradorient(idx) = atan(gradscaly(idx)./gradscalxplus(idx)) + pi;
idx = find(gradscalx >= 0 & gradscaly < 0); 
gradorient(idx) = atan(gradscaly(idx)./gradscalxplus(idx)) + 2*pi;
or = 2;
else 
error('Incorrect ISSIGNED parameter.');
end
end
% calculate block slide step.
xbstride = cellpw*nblockw*(1-overlap);
ybstride = cellph*nblockh*(1-overlap);
xbstridend = N - cellpw*nblockw + 1;
ybstridend = M - cellph*nblockh + 1;
% calculate the total blocks number in the window detected, which is ntotalbh*ntotalbw.
ntotalbh = ((M-cellph*nblockh)/ybstride)+1;
ntotalbw = ((N-cellpw*nblockw)/xbstride)+1;
% generate the matrix hist3dbig for storing the 3-dimensions histogram. the matrix covers the whole image in the 'globalinterpolate' condition or
% covers the local block in the 'localinterpolate' condition. The matrix is bigger than the area where it covers by adding additional elements
% (corresponding to the cells) to the surround for calculation convenience.
if strcmp(isglobalinterpolate, 'globalinterpolate') == 1 
ncellx = N / cellpw;
ncelly = M / cellph;
hist3dbig = zeros(ncelly+2, ncellx+2, nthet+2);
F = zeros(1, (M/cellph-1)*(N/cellpw-1)*nblockw*nblockh*nthet);
glbalinter = 1;
else
if strcmp(isglobalinterpolate, 'localinterpolate') == 1 
hist3dbig = zeros(nblockh+2, nblockw+2, nthet+2); 
F = zeros(1, ntotalbh*ntotalbw*nblockw*nblockh*nthet);
glbalinter = 0;
else
error('Incorrect ISGLOBALINTERPOLATE parameter.')
end
end
% generate the matrix for storing histogram of one block;
sF = zeros(1, nblockw*nblockh*nthet);
% generate gaussian spatial weight.
[gaussx, gaussy] = meshgrid(0:(cellpw*nblockw-1), 0:(cellph*nblockh-1));
weight = exp(-((gaussx-(cellpw*nblockw-1)/2).*(gaussx-(cellpw*nblockw-1)/2)+(gaussy-(cellph*nblockh-1)/2).*(gaussy-(cellph*nblockh-1)/2))/(delta*delta));
% vote for histogram. there are two situations according to the interpolate condition('global' interpolate or local interpolate). The hist3d which is
% generated from the 'bigger' matrix hist3dbig is the final histogram.
if glbalinter == 1
xbstep = nblockw*cellpw; 
ybstep = nblockh*cellph;
else
xbstep = xbstride;
ybstep = ybstride;
end
% block slide loop,其中btly與btlx分別表示block所在位置左上角點處的座標，(bj,bi)就是來存儲cell左上角的座標，(j,i)就表示cell中的像素在整個檢測窗（64*128的圖像）中的座標
for btly = 1:ybstep:ybstridend
for btlx = 1:xbstep:xbstridend
for bi = 1:(cellph*nblockh)
for bj = 1:(cellpw*nblockw)
i = btly + bi - 1;
j = btlx + bj - 1;
gaussweight = weight(bi,bj);
gs = gradscal(i,j);
go = gradorient(i,j);
%程序裏有個jorbj與iorbi，這在Localinterpolate的情況下（也就是標準的原始HOG情況），就是bj與bi.
if glbalinter == 1
jorbj = j;
iorbi = i;
else
jorbj = bj; 
iorbi = bi;
end
% calculate bin index of hist3dbig，hist3dbig這是一個三維的矩陣，用來存儲三維直方圖，計算八個統計區間中心點的座標
binx1 = floor((jorbj-1+cellpw/2)/cellpw) + 1;
biny1 = floor((iorbi-1+cellph/2)/cellph) + 1; 
binz1 = floor((go+(or*pi/nthet)/2)/(or*pi/nthet)) + 1;
if gs == 0 
continue;
end 
binx2 = binx1 + 1;
biny2 = biny1 + 1;
binz2 = binz1 + 1;
x1 = (binx1-1.5)*cellpw + 0.5;
y1 = (biny1-1.5)*cellph + 0.5;
z1 = (binz1-1.5)*(or*pi/nthet);
% trilinear interpolation.
%binx1，biny1，binz1在這裏就是那個八個bin塊之中離當前要統計的像素點在直方圖中對應的位置最接近的bin塊的下標；binx2，biny2，binz2對應就是最遠的bin塊的下標了
%x1,y1,z1就是bin塊(binx1，biny1，binz1)中心點對應的實際像素所在的位置（x1,y1）與梯度方向的角度(z1).
hist3dbig(biny1,binx1,binz1) =hist3dbig(biny1,binx1,binz1) + gs*gaussweight* (1-(jorbj-x1)/cellpw)*(1-(iorbi-y1)/cellph)*(1-(go-z1)/(or*pi/nthet));
hist3dbig(biny1,binx1,binz2) =hist3dbig(biny1,binx1,binz2) + gs*gaussweight* (1-(jorbj-x1)/cellpw)*(1-(iorbi-y1)/cellph)*((go-z1)/(or*pi/nthet)); 
hist3dbig(biny2,binx1,binz1) =hist3dbig(biny2,binx1,binz1) + gs*gaussweight* (1-(jorbj-x1)/cellpw)*((iorbi-y1)/cellph)*(1-(go-z1)/(or*pi/nthet));
hist3dbig(biny2,binx1,binz2) =hist3dbig(biny2,binx1,binz2) + gs*gaussweight* (1-(jorbj-x1)/cellpw)*((iorbi-y1)/cellph)*((go-z1)/(or*pi/nthet)); 
hist3dbig(biny1,binx2,binz1) =hist3dbig(biny1,binx2,binz1) + gs*gaussweight* ((jorbj-x1)/cellpw)*(1-(iorbi-y1)/cellph)*(1-(go-z1)/(or*pi/nthet));
hist3dbig(biny1,binx2,binz2) =hist3dbig(biny1,binx2,binz2) + gs*gaussweight* ((jorbj-x1)/cellpw)*(1-(iorbi-y1)/cellph)*((go-z1)/(or*pi/nthet));
hist3dbig(biny2,binx2,binz1) =hist3dbig(biny2,binx2,binz1) + gs*gaussweight* ((jorbj-x1)/cellpw)*((iorbi-y1)/cellph)*(1-(go-z1)/(or*pi/nthet));
hist3dbig(biny2,binx2,binz2) =hist3dbig(biny2,binx2,binz2) + gs*gaussweight* ((jorbj-x1)/cellpw)*((iorbi-y1)/cellph)*((go-z1)/(or*pi/nthet));
end
end
% In the local interpolate condition. F is generated in this block slide loop. hist3dbig should be cleared in each loop.
if glbalinter == 0
if or == 2
hist3dbig(:,:,2) = hist3dbig(:,:,2)+ hist3dbig(:,:,nthet+2);
hist3dbig(:,:,(nthet+1)) =hist3dbig(:,:,(nthet+1)) + hist3dbig(:,:,1); 
end
hist3d = hist3dbig(2:(nblockh+1), 2:(nblockw+1), 2:(nthet+1));
for ibin = 1:nblockh 
for jbin = 1:nblockw 
idsF = nthet*((ibin-1)*nblockw+jbin-1)+1; 
idsF = idsF:(idsF+nthet-1);
sF(idsF) = hist3d(ibin,jbin,:);
end 
end 
iblock = ((btly-1)/ybstride)*ntotalbw +((btlx-1)/xbstride) + 1;
idF = (iblock-1)*nblockw*nblockh*nthet+1; 
idF = idF:(idF+nblockw*nblockh*nthet-1);
F(idF) = sF;
hist3dbig(:,:,:) = 0;
end
end
end
% In the global interpolate condition. F is generated here outside the block slide loop 
if glbalinter == 1
ncellx = N / cellpw; 
ncelly = M / cellph;
if or == 2 
hist3dbig(:,:,2) = hist3dbig(:,:,2) + hist3dbig(:,:,nthet+2);
hist3dbig(:,:,(nthet+1)) = hist3dbig(:,:,(nthet+1)) + hist3dbig(:,:,1);
end
hist3d = hist3dbig(2:(ncelly+1), 2:(ncellx+1), 2:(nthet+1));
iblock = 1;
for btly = 1:ybstride:ybstridend
for btlx = 1:xbstride:xbstridend
binidx = floor((btlx-1)/cellpw)+1;
binidy = floor((btly-1)/cellph)+1;
idF = (iblock-1)*nblockw*nblockh*nthet+1; 
idF = idF:(idF+nblockw*nblockh*nthet-1);
for ibin = 1:nblockh 
for jbin = 1:nblockw 
idsF = nthet*((ibin-1)*nblockw+jbin-1)+1;
idsF = idsF:(idsF+nthet-1);
sF(idsF) = hist3d(binidy+ibin-1, binidx+jbin-1, :);
end
end
F(idF) = sF;
iblock = iblock + 1;
end
end
end
% adjust the negative value caused by accuracy of floating-point
% operations.these value's scale is very small, usually at E-03 magnitude
% while others will be E+02 or E+03 before normalization.F(F<0) = 0;
% block normalization.
e = 0.001;
l2hysthreshold = 0.2;
fslidestep = nblockw*nblockh*nthet;
switch normmethod
case 'none'
case 'l1'
for fi = 1:fslidestep:size(F,2)
div = sum(F(fi:(fi+fslidestep-1)));
F(fi:(fi+fslidestep-1)) = F(fi:(fi+fslidestep-1))/(div+e);
end
case 'l1sqrt'
for fi = 1:fslidestep:size(F,2) 
div = sum(F(fi:(fi+fslidestep-1))); 
F(fi:(fi+fslidestep-1)) = sqrt(F(fi:(fi+fslidestep-1))/(div+e));
end
case 'l2'
for fi = 1:fslidestep:size(F,2)
sF = F(fi:(fi+fslidestep-1)).*F(fi:(fi+fslidestep-1));
div = sqrt(sum(sF)+e*e);
F(fi:(fi+fslidestep-1)) = F(fi:(fi+fslidestep-1))/div;
end 
case 'l2hys'
for fi = 1:fslidestep:size(F,2)
sF = F(fi:(fi+fslidestep-1)).*F(fi:(fi+fslidestep-1)); 
div = sqrt(sum(sF)+e*e);
sF = F(fi:(fi+fslidestep-1))/div;
sF(sF>l2hysthreshold) = l2hysthreshold;
div = sqrt(sum(sF.*sF)+e*e);
F(fi:(fi+fslidestep-1)) = sF/div;
end
    otherwise 
error('Incorrect NORMMETHOD parameter.');
end
% the following code, which can be removed because of having no
% contributions to HOG feature calculation, are just for result
% demonstration when the trilinear interpolation is 'global' for this
% condition is easier to give a simple and intuitive illustration. so in
% 'local' condition ,it will produce error.
figure;
hold on;
axis equal;
xlim([0, N]);
ylim([0, M]);
for u = 1:(M/cellph) 
for v = 1:(N/cellpw)
cx = (v-1)*cellpw + cellpw/2 + 0.5;
cy = (u-1)*cellph + cellph/2 + 0.5;
hist3d(u,v,:)=0.9*min(cellpw,cellph)*hist3d(u,v,:)/max(hist3d(u,v,:));
for t = 1:nthet
s = hist3d(u,v,t);
thet = (t-1)*pi/nthet + pi*0.5/nthet;
x1 = cx - s*0.5*cos(thet);
x2 = cx + s*0.5*cos(thet);
y1 = cy - s*0.5*sin(thet);
y2 = cy + s*0.5*sin(thet);
plot([x1,x2],[M-y1+1,M-y2+1]);
end
end
end