…and shooting some Bieber outside of the school. The cops caught me, and this explains my recent absence from the world of blogging.
Actually, I took a little break because my inspiration had just about dried up. Working 70-hour weeks for three years does that to ya.
But I’m back, and I’ll keep posting about cool stuff that I make and do. Here’s one such thing:
This shows a comparison between two normalised sequences. The straighter and more diagonal the line, the closer the match. Dotted lines show periodic samples of time warping (note irregular spacing shows that warping has occurred in one direction or another). The difficulty here is making this understandable to a broad audience.
Here’s another sequence comparison, visualised differently. This time the graphs are overlaid (albeit offset) and time warping events are shown by the orange dots. If you can imagine a perfect match between two sequences, there would be no time warping and thus the orange lines would all be vertical. Add the overall ‘lengths’ of the orange lines and you get the 100% match ‘cost’. Now consider the above graph. The sum lengths of the orange lines indicate the ‘cost’ of the transformation. When comparing multiple queries against a single reference, the shortest ‘distance’ is the best match. Hey presto! Gesture recognition!