光流法测行人移动

修改了部分代码，并进行了计时以及某些代码的注释。

代码进行强角点检测，并将这些点的运动矢量以光流法绘制出来，并对不符合条件的运动矢量进行筛选。

/* --Sparse Optical Flow Demo Program--

* Written by David Stavens ([email protected])
*/
#include
#include
#include
#include


#include
using namespace std;


static const double pi = 3.14159265358979323846;


inline static double square(int a)
{
return a * a;
}


/* This is just an inline that allocates images.  I did this to reduce clutter in the
* actual computer vision algorithmic code.  Basically it allocates the requested image
* unless that image is already non-NULL.  It always leaves a non-NULL image as-is even
* if that image's size, depth, and/or channels are different than the request.
*/
inline static void allocateOnDemand(IplImage **img, CvSize size, int depth, int channels)
{
if (*img != NULL) return;


*img = cvCreateImage(size, depth, channels);
if (*img == NULL)
{
fprintf(stderr, "Error: Couldn't allocate image.  Out of memory?\n");
return;
}
}


int main(void)
{
/* Create an object that decodes the input video stream. */
CvCapture *input_video = cvCaptureFromFile(
"1.avi"
);
if (input_video == NULL)
{
/* Either the video didn't exist OR it uses a codec OpenCV
* doesn't support.
*/
fprintf(stderr, "Error: Can't open video.\n");
system("pause");
return -1;
}


/* Read the video's frame size out of the AVI. */
CvSize frame_size;
frame_size.height =
(int)cvGetCaptureProperty(input_video, CV_CAP_PROP_FRAME_HEIGHT);
frame_size.width =
(int)cvGetCaptureProperty(input_video, CV_CAP_PROP_FRAME_WIDTH);


/* Determine the number of frames in the AVI. */
long number_of_frames;
/* Go to the end of the AVI (ie: the fraction is "1") */
cvSetCaptureProperty(input_video, CV_CAP_PROP_POS_AVI_RATIO, 1.);
/* Now that we're at the end, read the AVI position in frames */
number_of_frames = (int)cvGetCaptureProperty(input_video, CV_CAP_PROP_POS_FRAMES);//视频的总帧数
/* Return to the beginning */
cvSetCaptureProperty(input_video, CV_CAP_PROP_POS_FRAMES, 0.);//设为第一帧状态


/* Create a windows called "Optical Flow" for visualizing the output.
* Have the window automatically change its size to match the output.
*/
cvNamedWindow("Optical Flow", CV_WINDOW_AUTOSIZE);


long current_frame = 0;
while (true)
{
double tick = cvGetTickCount();//计时函数

static IplImage *frame = NULL, *frame1 = NULL, *frame1_1C = NULL, *frame2_1C = NULL, *eig_image = NULL, *temp_image = NULL, *pyramid1 = NULL, *pyramid2 = NULL;

/* Go to the frame we want.  Important if multiple frames are queried in
* the loop which they of course are for optical flow.  Note that the very
* first call to this is actually not needed. (Because the correct position
* is set outsite the for() loop.)
*/
cvSetCaptureProperty(input_video, CV_CAP_PROP_POS_FRAMES, current_frame);//该句代码由于current的增加导致寻址变慢，会不断的增加代码时间
cout << (cvGetTickCount() - tick)/cvGetTickFrequency()/1000 << endl;
/* Get the next frame of the video.
* IMPORTANT!  cvQueryFrame() always returns a pointer to the _same_
* memory location.  So successive calls:
* frame1 = cvQueryFrame();
* frame2 = cvQueryFrame();
* frame3 = cvQueryFrame();
* will result in (frame1 == frame2 && frame2 == frame3) being true.
* The solution is to make a copy of the cvQueryFrame() output.
*/

frame = cvQueryFrame(input_video);
if (frame == NULL)
{
/* Why did we get a NULL frame?  We shouldn't be at the end. */
fprintf(stderr, "Error: Hmm. The end came sooner than we thought.\n");
return -1;
}

/* Allocate another image if not already allocated.
* Image has ONE channel of color (ie: monochrome) with 8-bit "color" depth.
* This is the image format OpenCV algorithms actually operate on (mostly).
*/
allocateOnDemand(&frame1_1C, frame_size, IPL_DEPTH_8U, 1);
/* Convert whatever the AVI image format is into OpenCV's preferred format.
* AND flip the image vertically.  Flip is a shameless hack.  OpenCV reads
* in AVIs upside-down by default.  (No comment :-))
*/
cvConvertImage(frame, frame1_1C, CV_CVTIMG_FLIP);


/* We'll make a full color backup of this frame so that we can draw on it.
* (It's not the best idea to draw on the static memory space of cvQueryFrame().)
*/
allocateOnDemand(&frame1, frame_size, IPL_DEPTH_8U, 3);
cvConvertImage(frame, frame1, CV_CVTIMG_FLIP);


/* Get the second frame of video.  Same principles as the first. */
frame = cvQueryFrame(input_video);
if (frame == NULL)
{
fprintf(stderr, "Error: Hmm. The end came sooner than we thought.\n");
return -1;
}
allocateOnDemand(&frame2_1C, frame_size, IPL_DEPTH_8U, 1);
cvConvertImage(frame, frame2_1C, CV_CVTIMG_FLIP);


/* Shi and Tomasi Feature Tracking! */


/* Preparation: Allocate the necessary storage. */
allocateOnDemand(&eig_image, frame_size, IPL_DEPTH_32F, 1);
allocateOnDemand(&temp_image, frame_size, IPL_DEPTH_32F, 1);


/* Preparation: This array will contain the features found in frame 1. */
CvPoint2D32f frame1_features[400];


/* Preparation: BEFORE the function call this variable is the array size
* (or the maximum number of features to find).  AFTER the function call
* this variable is the number of features actually found.
*/
int number_of_features;


/* I'm hardcoding this at 400.  But you should make this a #define so that you can
* change the number of features you use for an accuracy/speed tradeoff analysis.
*/
number_of_features = 400;


/* Actually run the Shi and Tomasi algorithm!!
* "frame1_1C" is the input image.
* "eig_image" and "temp_image" are just workspace for the algorithm.
* The first ".01" specifies the minimum quality of the features (based on the eigenvalues).
* The second ".01" specifies the minimum Euclidean distance between features.
* "NULL" means use the entire input image.  You could point to a part of the image.
* WHEN THE ALGORITHM RETURNS:
* "frame1_features" will contain the feature points.
* "number_of_features" will be set to a value <= 400 indicating the number of feature points found.
*/
cvGoodFeaturesToTrack(frame1_1C, eig_image, temp_image, frame1_features, &number_of_features, .01, .01, NULL);

/* Pyramidal Lucas Kanade Optical Flow! */


/* This array will contain the locations of the points from frame 1 in frame 2. */
CvPoint2D32f frame2_features[400];


/* The i-th element of this array will be non-zero if and only if the i-th feature of
* frame 1 was found in frame 2.
*/
char optical_flow_found_feature[400];


/* The i-th element of this array is the error in the optical flow for the i-th feature
* of frame1 as found in frame 2.  If the i-th feature was not found (see the array above)
* I think the i-th entry in this array is undefined.
*/
float optical_flow_feature_error[400];


/* This is the window size to use to avoid the aperture problem (see slide "Optical Flow: Overview"). */
CvSize optical_flow_window = cvSize(3, 3);


/* This termination criteria tells the algorithm to stop when it has either done 20 iterations or when
* epsilon is better than .3.  You can play with these parameters for speed vs. accuracy but these values
* work pretty well in many situations.
*/
CvTermCriteria optical_flow_termination_criteria
= cvTermCriteria(CV_TERMCRIT_ITER | CV_TERMCRIT_EPS, 20, .3);


/* This is some workspace for the algorithm.
* (The algorithm actually carves the image into pyramids of different resolutions.)
*/
allocateOnDemand(&pyramid1, frame_size, IPL_DEPTH_8U, 1);
allocateOnDemand(&pyramid2, frame_size, IPL_DEPTH_8U, 1);


/* Actually run Pyramidal Lucas Kanade Optical Flow!!
* "frame1_1C" is the first frame with the known features.
* "frame2_1C" is the second frame where we want to find the first frame's features.
* "pyramid1" and "pyramid2" are workspace for the algorithm.
* "frame1_features" are the features from the first frame.
* "frame2_features" is the (outputted) locations of those features in the second frame.
* "number_of_features" is the number of features in the frame1_features array.
* "optical_flow_window" is the size of the window to use to avoid the aperture problem.
* "5" is the maximum number of pyramids to use.  0 would be just one level.
* "optical_flow_found_feature" is as described above (non-zero iff feature found by the flow).
* "optical_flow_feature_error" is as described above (error in the flow for this feature).
* "optical_flow_termination_criteria" is as described above (how long the algorithm should look).
* "0" means disable enhancements.  (For example, the second array isn't pre-initialized with guesses.)
*/
cvCalcOpticalFlowPyrLK(frame1_1C, frame2_1C, pyramid1, pyramid2, frame1_features, frame2_features, number_of_features, optical_flow_window, 5, optical_flow_found_feature, optical_flow_feature_error, optical_flow_termination_criteria, 0);
//cout << frame2_features[25].x << endl;
/* For fun (and debugging :)), let's draw the flow field. */
for (int i = 0; i < number_of_features; i++)
{

/* If Pyramidal Lucas Kanade didn't really find the feature, skip it. */
if (optical_flow_found_feature[i] == 0) continue;


int line_thickness; line_thickness = 1;
/* CV_RGB(red, green, blue) is the red, green, and blue components
* of the color you want, each out of 255.
*/
CvScalar line_color; line_color = CV_RGB(255, 0, 0);


/* Let's make the flow field look nice with arrows. */


/* The arrows will be a bit too short for a nice visualization because of the high framerate
* (ie: there's not much motion between the frames).  So let's lengthen them by a factor of 3.
*/
CvPoint p, q;
p.x = (int)frame1_features[i].x;
p.y = (int)frame1_features[i].y;
q.x = (int)frame2_features[i].x;
q.y = (int)frame2_features[i].y;


double angle; angle = atan2((double)p.y - q.y, (double)p.x - q.x);
double hypotenuse; hypotenuse = sqrt(square(p.y - q.y) + square(p.x - q.x));
if (hypotenuse<3 || hypotenuse>20) continue;
/* Here we lengthen the arrow by a factor of three. */
q.x = (int)(p.x - 3 * hypotenuse * cos(angle));
q.y = (int)(p.y - 3 * hypotenuse * sin(angle));


/* Now we draw the main line of the arrow. */
/* "frame1" is the frame to draw on.
* "p" is the point where the line begins.
* "q" is the point where the line stops.
* "CV_AA" means antialiased drawing.
* "0" means no fractional bits in the center cooridinate or radius.
*/
cvLine(frame1, p, q, line_color, line_thickness, CV_AA, 0);
/* Now draw the tips of the arrow.  I do some scaling so that the
* tips look proportional to the main line of the arrow.
*/
p.x = (int)(q.x + 9 * cos(angle + pi / 4));
p.y = (int)(q.y + 9 * sin(angle + pi / 4));
cvLine(frame1, p, q, line_color, line_thickness, CV_AA, 0);//绘制箭头
p.x = (int)(q.x + 9 * cos(angle - pi / 4));
p.y = (int)(q.y + 9 * sin(angle - pi / 4));

cvLine(frame1, p, q, line_color, line_thickness, CV_AA, 0);//绘制箭头
}
/* Now display the image we drew on.  Recall that "Optical Flow" is the name of
* the window we created above.

*/

cvConvertImage(frame1, frame1, CV_CVTIMG_FLIP);

cvShowImage("Optical Flow", frame1);
/* And wait for the user to press a key (so the user has time to look at the image).
* If the argument is 0 then it waits forever otherwise it waits that number of milliseconds.
* The return value is the key the user pressed.
*/
int key_pressed=int("p");
//key_pressed = cvWaitKey(0);


/* If the users pushes "b" or "B" go back one frame.
* Otherwise go forward one frame.
*/
if (key_pressed == 'b' || key_pressed == 'B') current_frame--;
else current_frame++;
/* Don't run past the front/end of the AVI. */
if (current_frame < 0) current_frame = 0;
if (current_frame >= number_of_frames - 1) current_frame = number_of_frames - 2;
cvWaitKey(1);

cout << (cvGetTickCount() - tick) / cvGetTickFrequency()/1000 << endl;
}

}