我正在开展一个项目，我试图同时检测多个视频中的多个对象，我也在纠正视频中的失真，这样我就可以准确读取轴承检测相对于相机。
我使用Visual Studio 2010在C ++中使用OpenCV
代码有效，但速度很慢，不是实时。我希望有人可以提出建议，如果可以，可以加快速度。我目前没有太多的编码器和学习图像处理，也不知道很多技巧。
一般意义上代码的作用是：
- 暂停视频文件
- 对每个图像帧（轴承）应用失真校正
覆盖图像（改进检测，时间戳给出误报）
- 将Haar类型级联应用于裁剪图像以检测对象
- 在检测周围绘制一个边界框
- 显示图像
- 计算对象检测的角度并打印到终端
- 它还可以像雷达一样绘制图像，并在每个帧中显示相对于每个检测的相机的角度，我们的想法是将其作为单个源，在单个源上映射出每个摄像机的检测结果周边地区。
我已经包含了运行视频的主要代码和单个视频的检测，这仍然非常慢并需要大约。每秒视频18秒。当我有4个视频试图运行时，大约要长3倍。
视频尺寸为704x576。
任何帮助或建议都会非常感激，甚至只知道它只能用专门设计的硬件来加速。
干杯， 戴夫
int main(){
/////////////////////////////
//**Distortion Correction**//
/////////////////////////////
std::cout<< endl << "Reading:" << endl;
//stores a file
FileStorage fs;
//reads and stores the xml file with the camera calibration
fs.open("cal2.xml", FileStorage::READ);
if (fs.isOpened())
{
cout<<"File is opened\n";
}
//Mat objects to store the camera matrix and distortion coefficients
Mat CamMat, DistCoeff;
FileNode n = fs.root();
//takes the parameters from the xml file and stores them in the Mat objects
fs["Camera_Matrix"] >> CamMat;
fs["Distortion_Coefficients"] >> DistCoeff;
/////////////////////
//**Video Display**//
/////////////////////
//Mat objects to store the images
Mat Original, Vid1, Vid1Crop;
//Cropping Image to exclude time/camera stamps to improve detections
Rect roi(0, 35, 704, 490);
//for reading video or webcam
VideoCapture cap;
//for opening video file, give the location and name of the file seperating folders with "\\" instead of with a single "\"
cap.open("C:\\Users\\Desktop\\Run_01_005 two containers\\Video\\ch04_20140219124355.mp4");
//Windows for the images
namedWindow("New", CV_WINDOW_NORMAL);
namedWindow("Display", CV_WINDOW_NORMAL);
///////////////////////
//**Detection Setup**//
///////////////////////
// Cascade Classifier object
CascadeClassifier boat_cascade;
//loads the xml file for the classifier, put the address and name of the xml file in the brackets
boat_cascade.load( "boatcascadeAttp3.xml" );
/////////////////////////////////////
//**Single Source Display Image**////
/////////////////////////////////////
Mat Output;
//loop to continually capture/update images
while (1){
Output = Display();
cap>>Original;
//applies the distortion correction to input image and outputs to New image
undistort(Original, Vid1, CamMat, DistCoeff, noArray());
//Image excluding the time/camera stamps in video which caused a lot of false positives
Vid1Crop = Vid1(roi);
//Set.NewCrop(New, roi);
// Detect boats
std::vector<Rect> boats;
//Parameters may need some further adjustment, currently seems to work well
//Detection performed on Region of Interest that excludes the time stamp which caused a number of False Positives
boat_cascade.detectMultiScale( Vid1Crop, boats, 1.1, 15, 0|CV_HAAR_SCALE_IMAGE, Size(25, 25), Size(75,75) );
// Draw circles on the detected boats
for( int i = 0; i < boats.size(); i++ )
{
//Draws a box around the detected object
rectangle( Vid1Crop, Point(boats[i].x, boats[i].y), Point(boats[i].x+boats[i].width, boats[i].y+boats[i].height), Scalar( 0, 255, 0), 2, 8);
//finds the position of the detection along the X axis
int centreX = boats[i].x + boats[i].width*0.5;
int fromCent = Vid1Crop.cols - centreX;
float angle;
//calls Angle function
angle = Angle(centreX, fromCent, Vid1Crop);
//calls DisplayPoints function
Point XYpoints = DisplayPoints(angle);
//prints out the result, angle for cam ranges
cout << angle;
cout << " degrees" << endl;
//Draws red circles on the single source display corresponding to the detections
circle( Output, XYpoints, 5.0, Scalar( 0, 0, 255 ), 4, 8 );
}
//shows the New output image after correction
imshow("New", Vid1);
imshow("Display", Output);
//delay for 1ms between frames - Note 25 fps in video
waitKey(1);
}
fs.release();
return (0);
}