I want to do shot boundary detection via SVM's.
I'm dividing the frame into nxn blocks. Per block I'm finding these features:
shannons entropy edges (H,V,Diag) standard deviation
for consecutive frames and corresponding blocks, the above features are compared via differences and L2 norms, I threshold over that, if above threshold then given a 1 else 0. That is, the feature value belonging to that feature for that particular block becomes 1.
This assignment happens per feature for every block. For a frame, the feature vector is the summation of all the feature vectors of its blocks.
Then I take +-N/2 frames around it and concatenate their feature vectors to create a single feature vector (for that frame).
I trained the SVM using this. There are so many normal frames and only a few shot boundary frames. I'm dividing amongst cut,dissolve, fade, other and normal frames.
I'm unable to properly detect the shot boundaries.
Can someone suggest which features I should use and how I should select them for shot boundary detection? I think I may also have not done quite well on the threshold selection, so any ideas how I could do that better?
I'm using TRECVID's 2001/2002 database.