C++ 多尺度检测循环在OpenCV'中的工作原理；猪的检测？

在Dalal和Triggs关于猪的论文中，多尺度检测似乎是通过扫描图像金字塔来实现的。但是我找不到模块/objdetect/src/hog.cpp中执行金字塔扫描/循环的部分。是我的理解错误，还是我读取了错误的源文件？

如果您查看此函数的源代码

void HOGCache::init(const HOGDescriptor* _descriptor,
        const Mat& _img, Size _paddingTL, Size _paddingBR,
        bool _useCache, Size _cacheStride)

您将看到以下评论

// Initialize 2 lookup tables, pixData & blockData.
// Here is why:
//
// The detection algorithm runs in 4 nested loops (at each pyramid layer):
//  loop over the windows within the input image
//    loop over the blocks within each window
//      loop over the cells within each block
//        loop over the pixels in each cell
//
// As each of the loops runs over a 2-dimensional array,
// we could get 8(!) nested loops in total, which is very-very slow.
//
// To speed the things up, we do the following:
//   1. loop over windows is unrolled in the HOGDescriptor::{compute|detect} methods;
//         inside we compute the current search window using getWindow() method.
//         Yes, it involves some overhead (function call + couple of divisions),
//         but it's tiny in fact.
//   2. loop over the blocks is also unrolled. Inside we use pre-computed blockData[j]
//         to set up gradient and histogram pointers.
//   3. loops over cells and pixels in each cell are merged
//       (since there is no overlap between cells, each pixel in the block is processed once)
//      and also unrolled. Inside we use PixData[k] to access the gradient values and
//      update the histogram
//

正如注释所解释的，循环是为了优化而展开的，这也许就是为什么快速浏览源代码很难找到它们的原因