One of the things I studied in grad school was how to find the least visible seam in an image. This would be useful say if you overlapped two images and wanted to find the best way to cut them together, or if you wanted to create your own waldo image. I thought that the seam finding algorithms were really cool, but that there wasn’t a whole lot of use for them outside of doctoring photos and generating texture. Holy crap was I wrong. Check out this video:

This is the first time I’ve ever watched a technical video and thought to myself “I understand everything that is going on here… why didn’t I think of this!!” That’s a truly awesome idea. It makes me want to breakout my seam finding code and make an image resizer (I’ve written code that finds the low energy image seams you see in the video – it’s what I used to make the waldo image, which is the same image randomly pasted over and over again with a seam between overlapping areas).

The only problem with that idea is that finding seams isn’t as fast as they show you, at least not for large images (400+ by 400+). They might be using a different algorithm then what I’m thinking of, or maybe they were running the app on a super fast computer, but in my experience finding a seam can take some time if the image is of a decent size (by “some time” I mean 1 or 2 seconds). Though I might be wrong and this might be a super fast algorithm. It’ll be interesting to see how people apply this.