【OpenCV】人脸对齐landmark及位置姿态EstimateHeadPose（SDM）

SDM：https://github.com/RoboPai/sdm

 

#include "stdafx.h"

#include 
#include 
#include 


#include "opencv2/opencv.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/objdetect/objdetect.hpp"

#include "ldmarkmodel.h"

using namespace std;
using namespace cv;

int main()
{
	/*********************
	std::vector mImageLabels;
	if(!load_ImageLabels("mImageLabels-test.bin", mImageLabels)){
	mImageLabels.clear();
	ReadLabelsFromFile(mImageLabels, "labels_ibug_300W_test.xml");
	save_ImageLabels(mImageLabels, "mImageLabels-test.bin");
	}
	std::cout << "测试数据一共有: " <<  mImageLabels.size() << std::endl;
	*******************/

	ldmarkmodel modelt;
	std::string modelFilePath = "roboman-landmark-model.bin";
	while (!load_ldmarkmodel(modelFilePath, modelt)){
		std::cout << "文件打开错误，请重新输入文件路径." << std::endl;
		std::cin >> modelFilePath;
	}

	cv::VideoCapture mCamera(0);
	if (!mCamera.isOpened()){
		std::cout << "Camera opening failed..." << std::endl;
		system("pause");
		return 0;
	}
	cv::Mat Image;
	cv::Mat current_shape;
	for (;;){
		mCamera >> Image;
		modelt.track(Image, current_shape);
		cv::Vec3d eav;
		modelt.EstimateHeadPose(current_shape, eav);
		modelt.drawPose(Image, current_shape, 50);
	
		int numLandmarks = current_shape.cols / 2;
		for (int j = 0; j(j);
			int y = current_shape.at(j + numLandmarks);
			std::stringstream ss;
			ss << j;
			//            cv::putText(Image, ss.str(), cv::Point(x, y), 0.5, 0.5, cv::Scalar(0, 0, 255));
			cv::circle(Image, cv::Point(x, y), 2, cv::Scalar(0, 0, 255), -1);
		}
		cv::imshow("Camera", Image);
		if (27 == cv::waitKey(5)){
			mCamera.release();
			cv::destroyAllWindows();
			break;
		}
	}

	system("pause");
	return 0;
}

 

 

void ldmarkmodel::EstimateHeadPose(cv::Mat ¤t_shape, cv::Vec3d &eav){
    if(current_shape.empty())
        return;
    static const int samplePdim = 7;
    float miny = 10000000000.0f;
    float maxy = 0.0f;
    float sumx = 0.0f;
    float sumy = 0.0f;
    for(int i=0; i(estimateHeadPosePointIndexs[i]);
        float y = current_shape.at(estimateHeadPosePointIndexs[i]+current_shape.cols/2);
        sumy += y;
        if(miny > y)
            miny = y;
        if(maxy < y)
            maxy = y;
    }
    float dist = maxy - miny;
    sumx = sumx/samplePdim;
    sumy = sumy/samplePdim;
    static cv::Mat tmp(1, 2*samplePdim+1, CV_32FC1);
    for(int i=0; i(i) = (current_shape.at(estimateHeadPosePointIndexs[i])-sumx)/dist;
        tmp.at(i+samplePdim) = (current_shape.at(estimateHeadPosePointIndexs[i]+current_shape.cols/2)-sumy)/dist;
    }
    tmp.at(2*samplePdim) = 1.0f;
//    cv::Mat predict = tmp*estimateHeadPoseMat;
//    double _pm[12] = {predict.at(0), predict.at(1), predict.at(2), 0,
//                      predict.at(3), predict.at(4), predict.at(5), 0,
//                      predict.at(6), predict.at(7), predict.at(8), 0};
//    cv::Mat tmp0,tmp1,tmp2,tmp3,tmp4,tmp5;
//    cv::decomposeProjectionMatrix(cv::Mat(3,4,CV_64FC1,_pm),tmp0,tmp1,tmp2,tmp3,tmp4,tmp5,eav);
    cv::Mat predict = tmp*estimateHeadPoseMat2;
    eav[0] = predict.at(0);
    eav[1] = predict.at(1);
    eav[2] = predict.at(2);
//    std::cout << eav[0] << "  " << eav[1] << "  " << eav[2] << std::endl;
//    Pitch = eav[0];
//    Yaw	= eav[1];
//    Roll  = eav[2];
    return;
}

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