CvHaarFeature, CvHaarClassifier, CvHaarStageClassifier, CvHaarClassifierCascade
Boosted Haar 分类器结构

#define CV_HAAR_FEATURE_MAX 3

/* 一个 harr 特征由 2－3 个具有相应权重的矩形组成 */
/* a haar feature consists of 2-3 rectangles with appropriate weights */
typedef struct CvHaarFeature
{
    int tilted; /* 0 means up-right feature, 1 means 45--rotated feature */
   
    /* 2-3 rectangles with weights of opposite signs and
       with absolute values inversely proportional to the areas of the rectangles.
       if rect[2].weight !=0, then
       the feature consists of 3 rectangles, otherwise it consists of 2 */
    struct
    {
        CvRect r;
        float weight;
    } rect[CV_HAAR_FEATURE_MAX];
}
CvHaarFeature;

/* a single tree classifier (stump in the simplest case) that returns the response for the feature
   at the particular image location (i.e. pixel sum over subrectangles of the window) and gives out
   a value depending on the responce */
typedef struct CvHaarClassifier
{
    int count; /* number of nodes in the decision tree */

    /* these are "parallel" arrays. Every index i
       corresponds to a node of the decision tree (root has 0-th index).

       left[i] - index of the left child (or negated index if the left child is a leaf)
       right[i] - index of the right child (or negated index if the right child is a leaf)
       threshold[i] - branch threshold. if feature responce is <= threshold, left branch
                      is chosen, otherwise right branch is chosed.
       alpha[i] - output value correponding to the leaf. */
    CvHaarFeature* haar_feature;
    float* threshold;
    int* left;
    int* right;
    float* alpha;
}
CvHaarClassifier;

/* a boosted battery of classifiers(=stage classifier):
   the stage classifier returns 1
   if the sum of the classifiers' responces
   is greater than threshold and 0 otherwise */
typedef struct CvHaarStageClassifier
{
    int count; /* number of classifiers in the battery */
    float threshold; /* threshold for the boosted classifier */
    CvHaarClassifier* classifier; /* array of classifiers */

    /* these fields are used for organizing trees of stage classifiers,
       rather than just stright cascades */
    int next;
    int child;
    int parent;
}
CvHaarStageClassifier;

typedef struct CvHidHaarClassifierCascade CvHidHaarClassifierCascade;

/* cascade or tree of stage classifiers */
typedef struct CvHaarClassifierCascade
{
    int flags; /* signature */
    int count; /* number of stages */
    CvSize orig_window_size; /* original object size (the cascade is trained for) */

    /* these two parameters are set by cvSetImagesForHaarClassifierCascade */
    CvSize real_window_size; /* current object size */
    double scale; /* current scale */
    CvHaarStageClassifier* stage_classifier; /* array of stage classifiers */
    CvHidHaarClassifierCascade* hid_cascade; /* hidden optimized representation of the cascade,
                                                created by cvSetImagesForHaarClassifierCascade */
}
CvHaarClassifierCascade;

其中CvHaarFeature对应的就是haar特征，CvHaarClassifier是基于前面特征组成的弱分类器，CvHaarStageClassifier对应有弱分类器组成的强分类器，CvHaarStageClassifier对应最终的层叠分类器，理解这一点可以深刻的理解opencv下的adaboost人脸识别原理。