Detecting movement

After last week's class, we've implemented a way of detecting movement suggested by Serge. By subtracting the average background for each frame and binarizing the image, we can get a representation of movement.
We still need to work on the threshold used and clean up the blobs a bit, but it looks promising.

Here is the clip of blobs obtained from explore001 from set00:


Here are the blobs from groom001 from set00:


Current work:
1. Clean up our binary images, adjust the threshold to keep the number of blobs small.
2. Use each blob's centroid to create a displacement graph with respect to time in X and Y directions.
3. Create displacement prototypes based on these graphs by clustering them together.
4. Add this information to our behavior descriptor.