Function getFeatureMaps

roborts_tracking/KCFcpp/src/fhog.cpp:80–275

// Getting feature map for the selected subimage // // API // int getFeatureMaps(const IplImage * image, const int k, featureMap **map); // INPUT // image - selected subimage // k - size of cells // OUTPUT // map - feature map // RESULT // Error status */

// Error status
*/
int getFeatureMaps(const IplImage* image, const int k, CvLSVMFeatureMapCaskade **map)
{
    int sizeX, sizeY;
    int p, px, stringSize;
    int height, width, numChannels;
    int i, j, kk, c, ii, jj, d;
    float  * datadx, * datady;
    
    int   ch; 
    float magnitude, x, y, tx, ty;
    
    IplImage * dx, * dy;
    int *nearest;
    float *w, a_x, b_x;

    float kernel[3] = {-1.f, 0.f, 1.f};
    CvMat kernel_dx = cvMat(1, 3, CV_32F, kernel);
    CvMat kernel_dy = cvMat(3, 1, CV_32F, kernel);

    float * r;
    int   * alfa;
    
    float boundary_x[NUM_SECTOR + 1];
    float boundary_y[NUM_SECTOR + 1];
    float max, dotProd;
    int   maxi;

    height = image->height;
    width  = image->width ;

    numChannels = image->nChannels;

    dx    = cvCreateImage(cvSize(image->width, image->height), 
                          IPL_DEPTH_32F, 3);
    dy    = cvCreateImage(cvSize(image->width, image->height), 
                          IPL_DEPTH_32F, 3);

    sizeX = width  / k;
    sizeY = height / k;
    px    = 3 * NUM_SECTOR; 
    p     = px;
    stringSize = sizeX * p;
    allocFeatureMapObject(map, sizeX, sizeY, p);

    cvFilter2D(image, dx, &kernel_dx, cvPoint(-1, 0));
    cvFilter2D(image, dy, &kernel_dy, cvPoint(0, -1));
    
    float arg_vector;
    for(i = 0; i <= NUM_SECTOR; i++)
    {
        arg_vector    = ( (float) i ) * ( (float)(PI) / (float)(NUM_SECTOR) );
        boundary_x[i] = cosf(arg_vector);
        boundary_y[i] = sinf(arg_vector);
    }/*for(i = 0; i <= NUM_SECTOR; i++) */

    r    = (float *)malloc( sizeof(float) * (width * height));
    alfa = (int   *)malloc( sizeof(int  ) * (width * height * 2));