changed detection to opt flow

src/papillon.cpp

@@ -3,6 +3,7 @@
 #include <cv_bridge/cv_bridge.h>
 #include <sensor_msgs/image_encodings.h>
 #include <geometry_msgs/Twist.h>
+#include <typeinfo>
 
 #include <opencv/cv.h>
 
@@ -13,8 +14,8 @@ using namespace std;
 
 class Traite_image {
 	public:
-		const static int SENSITIVITY_VALUE = 30;
-		const static int BLUR_SIZE = 10;
+		const static int SENSITIVITY_VALUE = 10;
+		const static int BLUR_SIZE = 5;
 		
         
 		Mat prev;
@@ -70,7 +71,7 @@ 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);
             Mat next_stab_cropped = next_stab(myROI);
             Mat prev_cropped = prev(myROI);
-			searchForMovement(prev_cropped, next_stab_cropped, output);
+			searchForMovementOptFlow(prev_cropped, next_stab_cropped, output);
 
 
 			pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
@@ -180,6 +181,67 @@ class Traite_image {
 			//write the position of the object to the screen
 			putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2);
 		}
+        
+        void searchForMovementOptFlow(Mat prev, Mat cur, Mat &output){
+			Mat cur_grey, prev_grey;
+			cur.copyTo(output);
+			cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
+			cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
+            
+            Mat flow;
+            calcOpticalFlowFarneback(prev_grey, cur_grey, flow, 0.5, 3, 15, 3, 5, 1.2, 0);
+            vector<Mat> flow_coord(2); 
+            Mat flow_norm, angle;
+            split(flow, flow_coord);
+            cartToPolar(flow_coord[0], flow_coord[1], flow_norm, angle);
+            
+            //threshold(flow_norm, flow_norm, SENSITIVITY_VALUE, 255, THRESH_BINARY);
+			// Blur to eliminate noise
+			blur(flow_norm, flow_norm, Size(BLUR_SIZE, BLUR_SIZE));
+			threshold(flow_norm, flow_norm, SENSITIVITY_VALUE, 255, THRESH_BINARY);
+            flow_norm.convertTo(flow_norm, CV_8U);
+            
+            bool objectDetected = false;
+			Mat temp;
+			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
+			rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2);
+
+			//write the position of the object to the screen
+			putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2);
+		
+        }
+        
+        void get_norm(Mat coord, Mat &norm)
+        {
+            //for(i=0; i<
+        }
 
 		inline bool isFlowCorrect(Point2f u)
 		{