/* Trains the classifier on warps of a bounding-box patch.
frame: frame to take warps from
bb: first-frame bounding-box [x, y, width, height] */
void bbWarpPatch(IntegralImage *frame, double *bb) {
// Transformation matrix
float *m = new float[4];
// Loop through various rotations and skews
for (float r = -0.1f; r < 0.1f; r += 0.005f) {
float sine = sin(r);
float cosine = cos(r);
for (float sx = -0.1f; sx < 0.1f; sx += 0.05f) {
for (float sy = -0.1f; sy < 0.1f; sy += 0.05f) {
// Set transformation
/* Rotation matrix * skew matrix =
| cos r sin r | * | 1 sx | =
| -sin r cos r | | sy 1 |
| cos r + sy * sin r sx * cos r + sin r |
| sy * cos r - sin r cos r - sx * sin r | */
m[0] = cosine + sy * sine;
m[1] = sx * cosine + sine;
m[2] = sy * cosine - sine;
m[3] = cosine - sx * sine;
// Create warp and train classifier
IntegralImage *warp = new IntegralImage();
warp->createWarp(frame, bb, m);
classifier->train(warp, 0, 0, (int)bb[2], (int)bb[3], 1);
delete warp;
}
}
}
delete m;
}
// 用边框盒围住的小块的仿射变换来训练分类器
// frame: 输入的用于仿射变换的图像
// bb: 第一帧中的边框盒[x,y,width,height]
void bbWarpPatch(IntegralImage *frame, double *bb) {
// 变换矩阵
float *m = new float[4];
// 循环穿过各种旋转和斜交参数
for (float r = -0.1f; r < 0.1f; r += 0.005f) {
float sine = sin(r);
float cosine = cos(r);
for (float sx = -0.1f; sx < 0.1f; sx += 0.05f) {
for (float sy = -0.1f; sy < 0.1f; sy += 0.05f) {
// 设置转换矩阵
/* Rotation matrix * skew matrix =
| cos r sin r | * | 1 sx | =
| -sin r cos r | | sy 1 |
| cos r + sy * sin r sx * cos r + sin r |
| sy * cos r - sin r cos r - sx * sin r | */
m[0] = cosine + sy * sine;
m[1] = sx * cosine + sine;
m[2] = sy * cosine - sine;
m[3] = cosine - sx * sine;
// 创建仿射变换，然后训练分类器
IntegralImage *warp = new IntegralImage();
warp->createWarp(frame, bb, m);
classifier->train(warp, 1, 1, (int)bb[2], (int)bb[3], 1);
delete warp;
}
}
}
delete m;
}
