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Warp point vector helper

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lhark 2016-06-02 18:05:29 +02:00
parent a259a853e4
commit a488dbeec2
1 changed files with 41 additions and 51 deletions
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src/papillon.cpp
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@ -17,11 +17,17 @@ class Traite_image {
const static int THRESHOLD_DETECT_SENSITIVITY = 10; const static int THRESHOLD_DETECT_SENSITIVITY = 10;
const static int BLUR_SIZE = 5; const static int BLUR_SIZE = 5;
const static int THRESHOLD_MOV = 5; const static int THRESHOLD_MOV = 5;
const static int MOVEMENT_THRES = 0.1;
Mat prev; Mat prev;
Mat last_T; Mat last_T;
bool first = true; bool first = true;
// Features vectors
vector <Point2f> prev_ftr, cur_ftr;
// Downsize factor
int resize_f = 2; int resize_f = 2;
int theObject[2] = {0,0}; int theObject[2] = {0,0};
@ -72,7 +78,8 @@ class Traite_image {
Rect myROI(next_stab.size().width/8, next_stab.size().height/8, next_stab.size().width*3/4, next_stab.size().height*3/4); Rect myROI(next_stab.size().width/8, next_stab.size().height/8, next_stab.size().width*3/4, next_stab.size().height*3/4);
Mat next_stab_cropped = next_stab(myROI); Mat next_stab_cropped = next_stab(myROI);
Mat prev_cropped = prev(myROI); Mat prev_cropped = prev(myROI);
searchForMovementOptFlow(prev_cropped, next_stab_cropped, output); trackingOptFlow(prev_cropped, next_stab_cropped, output);
//searchForMovementOptFlow(prev_cropped, next_stab_cropped, output);
pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg()); pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
@ -109,14 +116,16 @@ class Traite_image {
calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err); calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
// weed out bad matches // weed out bad matches
prev_ftr.clear();
cur_ftr.clear();
for(size_t i=0; i < status.size(); i++) { for(size_t i=0; i < status.size(); i++) {
if(status[i]) { if(status[i]) {
prev_corner2.push_back(prev_corner[i]); prev_ftr.push_back(prev_corner[i]);
cur_corner2.push_back(cur_corner[i]); cur_ftr.push_back(cur_corner[i]);
} }
} }
Mat T = estimateRigidTransform(prev_corner2, cur_corner2, true); // false = rigid transform, no scaling/shearing Mat T = estimateRigidTransform(prev_ftr, cur_ftr, true); // false = rigid transform, no scaling/shearing
if(T.data == NULL) { if(T.data == NULL) {
last_T.copyTo(T); last_T.copyTo(T);
@ -239,59 +248,40 @@ class Traite_image {
} }
void trackingOptFlow(Mat prev, Mat cur, Mat &output) { void warpPoints(vector<Point2f> p, vector<Point2f> &p_warp, Mat T, bool invert=false) {
Mat cur_grey, prev_grey; if(invert)
cur.copyTo(output); invertAffineTransform(T, T);
cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
Mat flow; p_warp.clear();
calcOpticalFlowFarneback(prev_grey, cur_grey, flow, 0.5, 3, 15, 3, 5, 1.2, 0); for(size_t i=0; i < p.size(); ++i) {
vector<Mat> flow_coord(2); Mat src(3/*rows*/,1 /* cols */,CV_64F);
Mat flow_norm, angle;
split(flow, flow_coord);
cartToPolar(flow_coord[0], flow_coord[1], flow_norm, angle);
//threshold(flow_norm, flow_norm, THRESHOLD_DETECT_SENSITIVITY, 255, THRESH_BINARY); src.at<double>(0,0)=p[i].x;
// Blur to eliminate noise src.at<double>(1,0)=p[i].y;
blur(flow_norm, flow_norm, Size(BLUR_SIZE, BLUR_SIZE)); src.at<double>(2,0)=1.0;
threshold(flow_norm, flow_norm, THRESHOLD_DETECT_SENSITIVITY, 255, THRESH_BINARY);
flow_norm.convertTo(flow_norm, CV_8U);
bool objectDetected = false; Mat dst = T*src; //USE MATRIX ALGEBRA
Mat temp; p_warp.push_back(Point2f(dst.at<double>(0,0),dst.at<double>(1,0)));
flow_norm.copyTo(temp); }
//these two vectors needed for output of findContours
vector< vector<Point> > contours;
vector<Vec4i> hierarchy;
//find contours of filtered image using openCV findContours function
//findContours(temp,contours,hierarchy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE );// retrieves all contours
findContours(temp,contours,hierarchy,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE );// retrieves external contours
//if contours vector is not empty, we have found some objects
if(contours.size()>0)objectDetected=true;
else objectDetected = false;
if(objectDetected){
//the largest contour is found at the end of the contours vector
//we will simply assume that the biggest contour is the object we are looking for.
vector< vector<Point> > largestContourVec;
largestContourVec.push_back(contours.at(contours.size()-1));
//make a bounding rectangle around the largest contour then find its centroid
//this will be the object's final estimated position.
objectBoundingRectangle = boundingRect(largestContourVec.at(0));
} }
//make some temp x and y variables so we dont have to type out so much
int x = objectBoundingRectangle.x;
int y = objectBoundingRectangle.y;
int width = objectBoundingRectangle.width;
int height = objectBoundingRectangle.height;
//draw a rectangle around the object void trackingOptFlow(Mat prev, Mat cur, Mat &output) {
rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2); vector <Point2f> curc_stab;
Mat T = estimateRigidTransform(prev_ftr, cur_ftr, true); // false = rigid transform, no scaling/shearing
ROS_INFO("ready to warp");
warpPoints(cur_ftr, curc_stab, T, true);
ROS_INFO("warped");
//write the position of the object to the screen vector <Point2f> objects;
putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2); for(size_t i=0; i < prev_ftr.size(); ++i) {
float flow_norm = norm(prev_ftr[i] - cur_ftr[i]) / prev.size().height;
if(flow_norm > MOVEMENT_THRES)
objects.push_back(cur_ftr[i]);
}
for(size_t i=0; i < objects.size(); ++i) {
circle(output, objects[i], 5, Scalar(0, 200, 0), 1);
}
} }
inline bool isFlowCorrect(Point2f u) inline bool isFlowCorrect(Point2f u)