OpenCV reads the image sequence for hog pedestrian detection and saves it as a video __opencv

OpenCV Read the image sequence for hog pedestrian detection and saved as a video http://blog.csdn.net/masibuaa/article/details/16084467
2013-11-13 21:42 4273 People read comments (17) Collection Report Category: Computer Vision (OpenCV) Hog target detection (7)

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This program is used OPENCV default SVM parameters for detection, if the picture too much, processing will be slower.

[CPP]  View plain  copy #include  <stdio.h>   #include  <iostream>   # include <fstream>   #include  <opencv2/core/core.hpp>   #include   <opencv2/highgui/highgui.hpp>   #include  <opencv2/imgproc/imgproc.hpp>   # include <opencv2/objdetect/objdetect.hpp>   #include  <opencv2/ml/ml.hpp>       using namespace std;   using namespace cv;       Int main ()    {       Mat src;        string imgname;//picture file name        //ifstream fin ("Seq4List.txt") ;//Open Picture sequence file list        ifstream fin ("Subset.txt");          namedwindow ("Imageseq", 0);          videowriter videowriter;//Video Recorder        videowriter.open ("Seq6.avi", &NBSP;CV_FOURCC (' x ', ' V ', ' I ', ' D '), 25,size (1292,964))//Note If the picture size differs from the writer's size, it may fail        if (! Videowriter.isopened ())  cout<<  "Create Videowriter failed" <<endl;           hogdescriptor people_detect_hog; //hog Feature Detectors        // Using the default already trained SVM coefficients as the test model        people_detect_hog.setsvmdetector (hogdescriptor:: Getdefaultpeopledetector ());              while ( Getline (fin,imgname))        {            cout<< "Handling:" < found, found_filtered; //Rectangular Box Array             //of the imported images for multi-scale pedestrian detection, detection window moving step (8,8)             people_detect_hog.detectmultiscale (Src, found, 0, size (8), &NBSP;8),  size (32, 32),  1.05, 2);            //Find all the rectangular boxes that are not nested and put them in the found_filtered, and if there is nesting, take the outer largest rectangle box into the found_filtered             for (Int i=0; i < found.size ();  i++)            {                Rect r = found[i];                int j=0;              &