/** * @file ColorHistogramFeature.cpp * @brief histogram of oriented gradients ( dalal and triggs ) * @author Erik Rodner * @date 05/07/2008 */ #include #include "ColorHistogramFeature.h" #include "vislearning/cbaselib/FeaturePool.h" using namespace OBJREC; using namespace std; using namespace NICE; const double epsilon = 10e-8; /** simple constructor */ ColorHistogramFeature::ColorHistogramFeature( const Config *conf ) { window_size_x = conf->gI("ColorHistogramFeature", "window_size_x", 21 ); window_size_y = conf->gI("ColorHistogramFeature", "window_size_y", 21 ); scaleStep = conf->gD("ColorHistogramFeature", "scale_step", sqrt(2) ); numScales = conf->gI("ColorHistogramFeature", "num_scales", 5 ); int numBinsH = conf->gI("ColorHistogramFeature", "num_bins_h", 4); int numBinsS = conf->gI("ColorHistogramFeature", "num_bins_s", 2); int numBinsV = conf->gI("ColorHistogramFeature", "num_bins_v", 2); numBins = numBinsH*numBinsS*numBinsV; } /** simple destructor */ ColorHistogramFeature::~ColorHistogramFeature() { } double ColorHistogramFeature::val( const Example *example ) const { const NICE::MultiChannelImageT & img = example->ce->getDChannel ( CachedExample::D_INTEGRALCOLOR ); int tm_xsize = img.xsize; int tm_ysize = img.ysize; int xsize; int ysize; example->ce->getImageSize ( xsize, ysize ); int wsx2, wsy2; int exwidth = example->width; if ( exwidth == 0 ) { wsx2 = window_size_x * tm_xsize / (2*xsize); wsy2 = window_size_y * tm_ysize / (2*ysize); } else { int exheight = example->height; wsx2 = exwidth * tm_xsize / (2*xsize); wsy2 = exheight * tm_ysize / (2*ysize); } int xx, yy; xx = ( example->x ) * tm_xsize / xsize; yy = ( example->y ) * tm_ysize / ysize; assert ( (wsx2 > 0) && (wsy2 > 0) ); int xtl = xx - wsx2; int ytl = yy - wsy2; int xrb = xx + wsx2; int yrb = yy + wsy2; #define BOUND(x,min,max) (((x)<(min))?(min):((x)>(max)?(max):(x))) xtl = BOUND ( xtl, 0, tm_xsize - 1 ); ytl = BOUND ( ytl, 0, tm_ysize - 1 ); xrb = BOUND ( xrb, 0, tm_xsize - 1 ); yrb = BOUND ( yrb, 0, tm_ysize - 1 ); #undef BOUND assert ( bin < (int)img.numChannels ); assert ( img.data[bin] != NULL ); long kA = xtl + ytl * tm_xsize; long kB = xrb + ytl * tm_xsize; long kC = xtl + yrb * tm_xsize; long kD = xrb + yrb * tm_xsize; double A,B,C,D; A = img.data[bin][ kA ]; B = img.data[bin][ kB ]; C = img.data[bin][ kC ]; D = img.data[bin][ kD ]; double val1 = (D - B - C + A); double sum = val1*val1; for ( int b = 0 ; b < (int)img.numChannels ; b++) { if ( b == bin ) continue; A = img.data[b][ kA ]; B = img.data[b][ kB ]; C = img.data[b][ kC ]; D = img.data[b][ kD ]; double val = ( D - B - C + A ); sum += val*val; } sum = sqrt(sum); return ( val1 + epsilon ) / ( sum + epsilon ); } void ColorHistogramFeature::explode ( FeaturePool & featurePool, bool variableWindow ) const { int nScales = (variableWindow ? numScales : 1 ); for ( int i = 0 ; i < nScales ; i++ ) { int wsy = window_size_y; int wsx = window_size_x; for ( int _bin = 0 ; _bin < numBins ; _bin++ ) { ColorHistogramFeature *f = new ColorHistogramFeature(); f->window_size_x = wsx; f->window_size_y = wsy; f->bin = _bin; featurePool.addFeature ( f, 1.0 / ( numBins * nScales ) ); } wsx = (int) (scaleStep * wsx); wsy = (int) (scaleStep * wsy); } } Feature *ColorHistogramFeature::clone() const { ColorHistogramFeature *f = new ColorHistogramFeature(); f->window_size_x = window_size_x; f->window_size_y = window_size_y; f->bin = bin; return f; } Feature *ColorHistogramFeature::generateFirstParameter () const { return clone(); } void ColorHistogramFeature::restore (istream & is, int format) { is >> window_size_x; is >> window_size_y; is >> bin; } void ColorHistogramFeature::store (ostream & os, int format) const { os << "ColorHistogramFeature " << window_size_x << " " << window_size_y << " " << bin; } void ColorHistogramFeature::clear () { }