Opencv3.1 实现物体跟踪

本文主要是介绍Opencv3.1 实现物体跟踪，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

在本教程中，给大家介绍基于opencv3.1的目标跟踪的API， 我们将学习如何以及何时使用OpenCV 3.1中提供的6种不同的跟踪器-BOOSTING，MIL，KCF，TLD，MEDIANFLOW和GOTURN。 

#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <tracking/include/opencv2/tracking/tracker.hpp>void DataPrepare::openCameraAndPreview()
{Mat input_image;VideoCapture cam(0);if (!cam.isOpened()) exit(0);//cam.set(CV_CAP_PROP_FRAME_WIDTH, 864);//cam.set(CV_CAP_PROP_FRAME_HEIGHT, 480);double dWidth = cam.get(CV_CAP_PROP_FRAME_WIDTH); //输入流的宽double dHeight = cam.get(CV_CAP_PROP_FRAME_HEIGHT); //输入流的高cout << "Frame size : " << dWidth << " x " << dHeight << endl;namedWindow("摄像头");int detect = true;Ptr<Tracker> tracker = Tracker::create("BOOSTING");   //工程模式 创建不同的track：BOOSTING，MIL，KCF，TLD，MEDIANFLOW和GOTURN。 
//只需要执行两个方法， 1. init 初始化最初要跟踪的区域   2.update 有新的数据来之后更新 跟踪区域的位置实现跟踪

/*多目标跟踪使用的是MultiTracker，如MultiTracker myTracker("KCF")，注意两点，添加目标用其成员函数myTracker.add(Mat src, Rect2d roi)，获得跟踪结果使用myTracker.update(Mat src, vector<Rect2d> targets)，跟踪结果的序号即vector的序号。*/while (true) {cam >> input_image;double t0 = (double)cvGetTickCount();Rect2d face;if (detect){if (faceDetect(input_image, face)){detect = false;cout << face.x << "  " << face.y << "  " << face.width <<"  "<< face.height << endl;tracker->init(input_image, face);}}else {//使用物体跟踪//cout << face.x << face.y << face.width << face.height << endl;tracker->update(input_image, face);}double t1 = (double)cvGetTickCount();//cout << "cost is: " << ((t1 - t0) / ((double)cvGetTickFrequency() * 1000 * 1000)) * 1000 << "ms" << endl;cv::rectangle(input_image, face, Scalar(255,0,0));imshow("input image", input_image);if (27 == waitKey(30)){break;}}cam.release();}	注意两点，添加目标用其成员函数myTracker.add(Mat src, Rect2d roi)，获得跟踪结果使用myTracker.update(Mat src, vector<Rect2d> targets)，跟踪结果的序号即vector的序号。*/while (true) {cam >> input_image;double t0 = (double)cvGetTickCount();Rect2d face;if (detect){if (faceDetect(input_image, face)){detect = false;cout << face.x << "  " << face.y << "  " << face.width <<"  "<< face.height << endl;tracker->init(input_image, face);}}else {//使用物体跟踪//cout << face.x << face.y << face.width << face.height << endl;tracker->update(input_image, face);}double t1 = (double)cvGetTickCount();//cout << "cost is: " << ((t1 - t0) / ((double)cvGetTickFrequency() * 1000 * 1000)) * 1000 << "ms" << endl;cv::rectangle(input_image, face, Scalar(255,0,0));imshow("input image", input_image);if (27 == waitKey(30)){break;}}cam.release();}

 

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