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POHow to recognize a ball in an image and then model it in 3D(HawkEye System)
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copied!<p><br> We are trying to develop HawkEye System used in cricket for our college project. The process used in HawkEye System is as follows: </p> <ol> <li>images of the the ball at different instances of time(different points) from bowler's hand to the batsmen's(during entire flight of the ball) are needed </li> <li>determining the (x,y) coordinates of the ball at different instances of time during the entire flight of the ball </li> <li>converting the (x,y) coordinates into the corresponding 3D coordinates (x,y,z) </li> <li>modelling the trajectory of the ball during the entire flight of the ball along with the surrounding environment of the ball which includes field, pitch, wickets, stadium </li> <li>extending the trajectory of the ball to see whether the ball would have hit the wickets or not </li> </ol> <p>So far this is what we've planned to accomplish this project: </p> <p>we'll shoot the video of the batsman from the leg umpire's position and then play that video in slow motion in vlc player and simultaneously taking multiple screenshots of the flight of the ball, i guess this will take care of the step 1.</p> <p>but right now we are stuck in step 2, the problem which we're facing now is that how to recognize and find the (x,y) coordinate of the ball at a particular instance (from the image of the ball taken from leg side) if we can find the (x,y) of the ball and if the distance of the camera from some reference point is known then we can find the depth of the image i.e. the z-coordinate, hence we can find out the corresponding (x,y,z) coordinates and then we can model it in 3D using OpenGL</p> <p>we're trying to implement it in C++ </p> <p>any help appreciated :)</p> <p>A quick edit:<br> I came to know that in real HawkEye System 6 cameras are adjusted on the circumference of the cricket field, all the cameras are seperated by an angle of 60 degree, HawkEye can work perfectly using 4 cameras only but for better precision 2 extra cameras are used. since we dont have so many cameras, I think we'll be using 3 cameras kept on the circumference of the field seperated by 120 degrees and to reduce the complexity we'll be choosing a small field may be one with radius=5m, but we're not sure where to place the cameras to get more accurate results, may be the positions can be: one on the legside, one on off-side and the third one straight in front but i'm still not sure what positions to choose</p> <p>this approach is called Multi Camera Calibration and for ball recognition I think we should choose OpenCV over MATLAB because of more speedy image processing done by OpenCV </p> <p>What do you all have to say?</p>

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