I must say I am pretty impressed with the results. Certainly pinpointing the person in the middle frame of figure 10 is a great success (I totally agree with Sunny - I can't hardly see the person!). Anyway, ever since we have been presented with the idea of "sprites" since earlier this quarter, my interest has grown in this area. I think that by segmenting out certain part of an image and building them up as layers is a step in the right direction to classifying objects and motion.

One interesting things that I noticed was that they have made all background layers share the same motion. In most cases, I can see that this should work. However, I can imagine a scenario where a background object moves independent of the other background objects. Let's say that the camera is focused on a harbor watching boats leave. The primary application would probably be to watch when certain boats come and go. However, what if there is a buoy in the water that is bobbing up and down that should be part of the background? I guess the buoy could be made part of the foreground but then you would be tracking an undesirable object. It seems that in future work they could adapt a model in which the background layers are a bit "deformable" meaning that each layer would have a little freedom to move. However, such a model would have to be careful not to eliminate objects that are moving about as slow as the deformation would allow. Anyway, it is an interesting problem and I look forward to what future papers have to say regarding this.