Particle Filter Model for Computer Vision Tracking - vision

Question

I see alot of posts for particle filters for such purposes, but none of them talk about the steps. Most tutorials online are for Kinematic Models involving R,Theta movements.
I want to use a particle filter to track a simple yellow blob. It is noisy as it's underwater, and at times may be occluded. How would I implement a model for this, and what might the "move" function of the object be?

Answer 1

You can use optical flow in order to detect the direction of movement.
This is how I do it:
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
static const double pi = 3.14159265358979323846;
inline static double square(int a)
{
return a * a;
}
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");
exit(-1);
}
}
int main(void)
{
CvCapture *input_video = cvCaptureFromCAM(0);
if (input_video == NULL)
{
fprintf(stderr, "Error: Can't open video.\n");
return -1;
}
cvQueryFrame( input_video );
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 );
long number_of_frames;
cvSetCaptureProperty( input_video, CV_CAP_PROP_POS_AVI_RATIO, 1. );
number_of_frames = (int) cvGetCaptureProperty( input_video, CV_CAP_PROP_POS_FRAMES );
cvSetCaptureProperty( input_video, CV_CAP_PROP_POS_FRAMES, 0. );
cvNamedWindow("Optical Flow", CV_WINDOW_AUTOSIZE);
long current_frame = 0;
while(true)
{
static IplImage *frame = NULL, *frame1 = NULL, *frame1_1C = NULL, *frame2_1C =
NULL, *eig_image = NULL, *temp_image = NULL, *pyramid1 = NULL, *pyramid2 = NULL;
cvSetCaptureProperty( input_video, CV_CAP_PROP_POS_FRAMES, current_frame );
frame = cvQueryFrame( input_video );
if (frame == NULL)
{
fprintf(stderr, "Error: Hmm. The end came sooner than we thought.\n");
return -1;
}
allocateOnDemand( &frame1_1C, frame_size, IPL_DEPTH_8U, 1 );
cvConvertImage(frame, frame1_1C, CV_CVTIMG_FLIP);
allocateOnDemand( &frame1, frame_size, IPL_DEPTH_8U, 3 );
cvConvertImage(frame, frame1, CV_CVTIMG_FLIP);
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);
allocateOnDemand( &eig_image, frame_size, IPL_DEPTH_32F, 1 );
allocateOnDemand( &temp_image, frame_size, IPL_DEPTH_32F, 1 );
CvPoint2D32f frame1_features[400];
int number_of_features;
number_of_features = 400;
cvGoodFeaturesToTrack(frame1_1C, eig_image, temp_image, frame1_features, &
number_of_features, .01, .01, NULL);
CvPoint2D32f frame2_features[400];
char optical_flow_found_feature[400];
float optical_flow_feature_error[400];
CvSize optical_flow_window = cvSize(3,3);
CvTermCriteria optical_flow_termination_criteria
= cvTermCriteria( CV_TERMCRIT_ITER | CV_TERMCRIT_EPS, 20, .3 );
allocateOnDemand( &pyramid1, frame_size, IPL_DEPTH_8U, 1 );
allocateOnDemand( &pyramid2, frame_size, IPL_DEPTH_8U, 1 );
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 );
for(int i = 0; i < number_of_features; i++)
{
if ( optical_flow_found_feature[i] == 0 ) continue;
int line_thickness; line_thickness = 1;
CvScalar line_color; line_color = CV_RGB(255,0,0);
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) );
q.x = (int) (p.x - 3 * hypotenuse * cos(angle));
q.y = (int) (p.y - 3 * hypotenuse * sin(angle));
cvLine( frame1, p, q, line_color, line_thickness, CV_AA, 0 );
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 );
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 );
}
cvShowImage("Optical Flow", frame1);
int key_pressed;
key_pressed = cvWaitKey(0);
if (key_pressed == 'b' || key_pressed == 'B') current_frame--;
else current_frame++;
if (current_frame < 0) current_frame = 0;
if (current_frame >= number_of_frames - 1) current_frame = number_of_frames - 2;
}
}