Scratch Input and Low-Cost Multi-spectral material sensor

Chris Harrison, a PhD Student at my old program at CMU, presented a couple projects of his at UIST 2008 that I really really like. The first is his "Scratch Input" device. The basic idea is that if you place a senstive microphone on the bottom of a mobile device. Any large, hard surface you put it down on can now be used as an input gesture surface. A variety of gestures can be distinctly and reliably detected with some simple machine learning. Video (academic) below include a nice demo where he turns his entire wall into an MP3 player controller:



The other project he presented was a simple, cheap multi-spectral sensor for recognizing various materials. It includes an IR LED, UV LED, RGB LED, a photoresistor, and a TSL230 TOAS optical sensor. With these, he read the reflectively under different illuminations to recognize 27 different materials with 86.9% accuracy, be this your jeans, your backpack, your desk at home, your desk at work. This means coarse location awareness of mobile devices for cheap, some opportunities for more intelligent power management, and implicit security behaviors when placed on familiar or unfamiliar surfaces. Very nice work.