flandmark是一個檢測臉部特徵點的開原始碼庫(http://cmp.felk.cvut.cz/~uricamic/flandmark/), 利用flandmark可以檢測到左右眼睛的左右角點、鼻子、嘴的左右角點，位置如下：

/*
*    5   1    2   6
*
*
*          0/7
*
*
*       3       4
*
*/

檢測效果如下圖：

對於兩幅臉部影象，檢測到各自臉部特徵點後，可以利用其中的三個對應特徵點，進行仿射變換，將兩幅臉部影象對齊。

程式碼：

#include "libflandmark/flandmark_detector.h"
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/highgui/highgui.hpp>
using namespace cv;

#define _DEBUG_INFO

int detectFaceInImage(IplImage *orig, IplImage* input, CvHaarClassifierCascade* cascade, FLANDMARK_Model *model, int *bbox, double *landmarks)
{
	int ret = 0;

    // Smallest face size.
    CvSize minFeatureSize = cvSize(40, 40);
    int flags =  CV_HAAR_DO_CANNY_PRUNING;
    // How detailed should the search be.
    float search_scale_factor = 1.1f;
    CvMemStorage* storage;
    CvSeq* rects;
    int nFaces;

    storage = cvCreateMemStorage(0);
    cvClearMemStorage(storage);

    // Detect all the faces in the greyscale image.
    rects = cvHaarDetectObjects(input, cascade, storage, search_scale_factor, 2, flags, minFeatureSize);
    nFaces = rects->total;

    double t = (double)cvGetTickCount();
    for (int iface = 0; iface < (rects ? nFaces : 0); ++iface)
    {
        CvRect *r = (CvRect*)cvGetSeqElem(rects, iface);
        
        bbox[0] = r->x;
        bbox[1] = r->y;
        bbox[2] = r->x + r->width;
        bbox[3] = r->y + r->height;
        
        ret = flandmark_detect(input, bbox, model, landmarks);

#ifdef _DEBUG_INFO
        // display landmarks
        cvRectangle(orig, cvPoint(bbox[0], bbox[1]), cvPoint(bbox[2], bbox[3]), CV_RGB(255,0,0) );
        cvRectangle(orig, cvPoint(model->bb[0], model->bb[1]), cvPoint(model->bb[2], model->bb[3]), CV_RGB(0,0,255) );
        cvCircle(orig, cvPoint((int)landmarks[0], (int)landmarks[1]), 3, CV_RGB(0, 0,255), CV_FILLED);
        for (int i = 2; i < 2*model->data.options.M; i += 2)
        {
            cvCircle(orig, cvPoint(int(landmarks[i]), int(landmarks[i+1])), 3, CV_RGB(255,0,0), CV_FILLED);

        }
#endif

    }
    t = (double)cvGetTickCount() - t;
    int ms = cvRound( t / ((double)cvGetTickFrequency() * 1000.0) );

    if (nFaces > 0)
    {
        printf("Faces detected: %d; Detection of facial landmark on all faces took %d ms\n", nFaces, ms);
    } else {
        printf("NO Face\n");
		ret = -1;
    }
    
    cvReleaseMemStorage(&storage);

	return ret;
}

/*
*    5   1    2   6	
*
*
*          0/7
*
*
*       3       4
*
*/


int main( int argc, char** argv ) 
{
     
    if (argc != 3)
    {
      fprintf(stderr, "Usage: %s <src_image> <dst_image>\n", argv[0]);
      exit(1);
    }
    
    
    
    // Haar Cascade file, used for Face Detection.
    char faceCascadeFilename[] = "haarcascade_frontalface_alt.xml";
    // Load the HaarCascade classifier for face detection.
    CvHaarClassifierCascade* faceCascade;
    faceCascade = (CvHaarClassifierCascade*)cvLoad(faceCascadeFilename, 0, 0, 0);
    if( !faceCascade )
    {
        printf("Couldnt load Face detector '%s'\n", faceCascadeFilename);
        exit(1);
    }

     // ------------- begin flandmark load model
    double t = (double)cvGetTickCount();
    FLANDMARK_Model * model = flandmark_init("flandmark_model.dat");
    if (model == 0)
    {
        printf("Structure model wasn't created. Corrupted file flandmark_model.dat?\n");
        exit(1);
    }
    t = (double)cvGetTickCount() - t;
    double ms = cvRound( t / ((double)cvGetTickFrequency() * 1000.0) );
    printf("Structure model loaded in %d ms.\n", ms);
    // ------------- end flandmark load model
    
    // input image
    IplImage *src = cvLoadImage(argv[1]);
	IplImage *dst = cvLoadImage(argv[2]);
    if (src == NULL)
    {
      fprintf(stderr, "Cannot open image %s. Exiting...\n", argv[1]);
      exit(1);
    }
	if (dst == NULL)
    {
      fprintf(stderr, "Cannot open image %s. Exiting...\n", argv[2]);
      exit(1);
    }

    // convert image to grayscale
    IplImage *src_gray = cvCreateImage(cvSize(src->width, src->height), IPL_DEPTH_8U, 1);
    cvConvertImage(src, src_gray);
	IplImage *dst_gray = cvCreateImage(cvSize(dst->width, dst->height), IPL_DEPTH_8U, 1);
    cvConvertImage(dst, dst_gray);
    
	// detect landmarks
    int *bbox_src = (int*)malloc(4*sizeof(int));
	int *bbox_dst = (int*)malloc(4*sizeof(int));
    double *landmarks_src = (double*)malloc(2*model->data.options.M*sizeof(double));
	double *landmarks_dst = (double*)malloc(2*model->data.options.M*sizeof(double));
    int ret_src = detectFaceInImage(src, src_gray, faceCascade, model, bbox_src, landmarks_src);
	int ret_dst = detectFaceInImage(dst, dst_gray, faceCascade, model, bbox_dst, landmarks_dst);
    if(0 != ret_src || 0 != ret_dst){
		printf("Landmark not detected!\n");
		return -1;
	}


	// *** face alignment begin *** //
	Point2f srcTri[3];
	Point2f dstTri[3];
	Mat src_mat(src);
	Mat dst_mat(dst);
	Mat warp_mat( 2, 3, CV_32FC1 );
	Mat warp_dst;

	/// Set the dst image the same type and size as src
	warp_dst = Mat::zeros( src_mat.rows, src_mat.cols, src_mat.type() );

	/// Set your 3 points to calculate the  Affine Transform
	srcTri[0] = Point2f( landmarks_src[5*2], landmarks_src[5*2+1] );
	srcTri[1] = Point2f( landmarks_src[6*2], landmarks_src[6*2+1] );
	srcTri[2] = Point2f( landmarks_src[0*2], landmarks_src[0*2+1] );

	dstTri[0] = Point2f( landmarks_dst[5*2], landmarks_dst[5*2+1] );
	dstTri[1] = Point2f( landmarks_dst[6*2], landmarks_dst[6*2+1] );
	dstTri[2] = Point2f( landmarks_dst[0*2], landmarks_dst[0*2+1] );

	/// Get the Affine Transform
	warp_mat = getAffineTransform( srcTri, dstTri );

	/// Apply the Affine Transform just found to the src image
	warpAffine( src_mat, warp_dst, warp_mat, warp_dst.size() );
	// *** face alignment end *** //

	// show images
	imshow("src", src_mat);
	imshow("dst", dst_mat);
	imshow("warp_dst", warp_dst);
	//imwrite("src.jpg", src_mat);
	//imwrite("dst.jpg", dst_mat);
	//imwrite("warp_dst.jpg", warp_dst);
	waitKey(0);



    // cleanup
    free(bbox_src);
    free(landmarks_src);
	free(bbox_dst);
    free(landmarks_dst);
    cvDestroyAllWindows();
    cvReleaseImage(&src);
    cvReleaseImage(&src_gray);
	cvReleaseImage(&dst);
    cvReleaseImage(&dst_gray);
    cvReleaseHaarClassifierCascade(&faceCascade);
    flandmark_free(model);
}