More Club Detection

We've worked on club detection to make it work for a better sample video of a full golf swing (in slow motion). We adjusted the threshold for the LO Hough transform, so that it still gets good signal around the club but not as much erroneous signal. We also realized that for the HI lines, we were getting a lot of good signal but we were pruning too much of it out. We've made the filtering process for HI a little better, but there are still ways to make it better to retain even more HI signal (e.g, working harder to merge parallel and disconnected segments).

We've also estimated the top of the backswing using a simple metric. For each frame, we consider the best single hypothesis for the club position. We then look for places where the 2nd derivative between 2 frames is 0, and choose these frames as possiblilities for the transition from upswing to backswing. We then use a weighting scale to assign each of these possibilities a score, based on distance from the middle of the sequence and the number of surrounding LO hypotheses. We then choose the frame with the lowest score.

The changes to Hough thresholding and detection of the transition work pretty well on the following video.



Upswing:



Downswing:



The hypotheses for the clubhead (marked by white circles) are fairly accurate, so we should be able to get a good polynomial approximation using least squares and RANSAC.

We also need to develop a library of test videos, with different conditions, so that we can be confident that the refinements we are making are robust.