Tracking Over Many Frames
	Feature tracking with m frames 1. Select features in first frame 2. Given feature in frame i, compute position in i+1 3. Select more features if needed 4. i = i + 1 5. If i < m, go to step 2
	Issues • Discrete search vs. Lucas Kanade? – depends on expected magnitude of motion – discrete search is more flexible • Compare feature in frame i to i+1 or frame 1 to i+1? – affects tendency to drift.. • How big should search window be? – too small:  lost features.  Too large:  slow