Opencv Open实时摄像头，但不是网络摄像头（Windows）

Question

我在opencv上学习冲浪我可以成功运行我的代码但是我的相机不是网络摄像头我正在使用ricoh theta s我可以在我的电脑中实时成功打开这台相机另一方面我无法打开这台相机opencv我的代码总是打开我的网络摄像头我想在我的代码中打开ricoh theta相机如何用我的代码实时打开这个相机 （我尝试过VideoCapture cap（1）但我的网络摄像头再次打开但是其他相机没有打开） 我的代码在这里：

    #include <iostream>
#include <stdio.h>
#include <iostream>
#include <fstream>
#include <string>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/legacy/legacy.hpp"
#include "opencv2/imgproc/imgproc.hpp"


using namespace cv;
using namespace std;


char key = 'a';
int framecount = 0;


SurfFeatureDetector detector( 500 );
SurfDescriptorExtractor extractor;
FlannBasedMatcher matcher;

Mat frame, des_object, image;
Mat des_image, img_matches, H;

std::vector<KeyPoint> kp_object;
std::vector<Point2f> obj_corners(4);
std::vector<KeyPoint> kp_image;
std::vector<vector<DMatch > > matches;
std::vector<DMatch > good_matches;
std::vector<Point2f> obj;
std::vector<Point2f> scene;
std::vector<Point2f> scene_corners(4);

int main()
{             
                //reference image
    Mat object = imread( "C:\\OpenCV2.4.6\\hazmat.png", CV_LOAD_IMAGE_GRAYSCALE );

    if( !object.data )
    {
        std::cout<< "Error reading object " << std::endl;
        return -1;
    }

                //compute detectors and descriptors of reference image
    detector.detect( object, kp_object );
    extractor.compute( object, kp_object, des_object );     

                //create video capture object
    VideoCapture cap(1);
   // VideoCapture cap2()

    //Get the corners from the object
    obj_corners[0] = cvPoint(0,0);
    obj_corners[1] = cvPoint( object.cols, 0 );
    obj_corners[2] = cvPoint( object.cols, object.rows );
    obj_corners[3] = cvPoint( 0, object.rows );

                //wile loop for real time detection
    while (key != 27)
    {
                                //capture one frame from video and store it into image object name 'frame'
        cap >> frame;

        if (framecount < 5)
        {
            framecount++;
            continue;
        }      

                                //converting captured frame into gray scale
        cvtColor(frame, image, CV_RGB2GRAY);

                                //extract detectors and descriptors of captured frame
                                detector.detect( image, kp_image );
                                extractor.compute( image, kp_image, des_image );

                                //find matching descriptors of reference and captured image
                                matcher.knnMatch(des_object, des_image, matches, 2);

                                //finding matching keypoints with Euclidean distance 0.6 times the distance of next keypoint
                                //used to find right matches
                                for(int i = 0; i < min(des_image.rows-1,(int) matches.size()); i++)
                                {
                                                if((matches[i][0].distance < 0.6*(matches[i][1].distance)) && ((int) matches[i].size()<=2 && (int) matches[i].size()>0))
                                                {
                                                                good_matches.push_back(matches[i][0]);
                                                }
                                }                             

                                //Draw only "good" matches
                                drawMatches( object, kp_object, frame, kp_image, good_matches, img_matches,
                                                Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

                                //3 good matches are enough to describe an object as a right match.
                                if (good_matches.size() >= 3)
        {                                     

            for( int i = 0; i < good_matches.size(); i++ )
            {
                //Get the keypoints from the good matches
                obj.push_back( kp_object[ good_matches[i].queryIdx ].pt );
                scene.push_back( kp_image[ good_matches[i].trainIdx ].pt );
            }
                                                try
                                                {
                                                                H = findHomography( obj, scene, CV_RANSAC );
                                                }
                                                catch(Exception e){}

            perspectiveTransform( obj_corners, scene_corners, H);

            //Draw lines between the corners (the mapped object in the scene image )
            line( img_matches, scene_corners[0] + Point2f( object.cols, 0), scene_corners[1] + Point2f( object.cols, 0), Scalar(0, 255, 0), 4 );
            line( img_matches, scene_corners[1] + Point2f( object.cols, 0), scene_corners[2] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
            line( img_matches, scene_corners[2] + Point2f( object.cols, 0), scene_corners[3] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
            line( img_matches, scene_corners[3] + Point2f( object.cols, 0), scene_corners[0] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
        }

        //Show detected matches
        imshow( "Good Matches", img_matches );

                                //clear array
                                good_matches.clear();

        key = waitKey(1);
    }
    return 0;
}