Colin’s mid-semester pre­sen­ta­tion has me think­ing about sound and image. Now that it’s on my mind, I see inter­est­ing exam­ples everywhere.

First, mak­ing music with your face:

Next, build­ing a visual land­scape with sound. (Watch it in low-res below, or in high-definition on Vimeo.)

Finally! Someone makes fun of CNN’s gra­tu­itous and dis­tract­ing use of mul­ti­touch tech­nol­ogy to dis­play data that would be much more clearly com­mu­ni­cated through sim­ple sta­tic dis­plays. Thanks, SNL! (Hint: Jump to 1:30 into the video.)

For my next project at Berkeley, I cre­ated a real time visu­al­iza­tion of esti­mated train arrival times within the BART sys­tem. So next time you need to head over to the East Bay, just check the visu­al­iza­tion and you can see how far away your train is from the station.

More detail on the project and process behind it are doc­u­mented here. Thanks to BART for mak­ing their arrivals data available!

Launch project >

Here’s a video demo of my iTunes Library Visualization project. I rec­om­mend watch­ing it in HD on Vimeo—click the outward-pointing arrows to make it full-screen and then click “HD” to get the best qual­ity image. (You can also play it above, at low-quality.)

Each track is rep­re­sented by a disc. Longer tracks are larger discs. The tracks can be orga­nized in space by length and fre­quency of play­back (i.e. most listened-to tracks fly toward the front, least listened-to recede). Grouping by genre adds color and clus­ters all tracks of the same genre around one point. Once the tracks are col­orized, they can be reordered while main­tain­ing the color (so, for exam­ple, you could see if you lis­ten to jazz more often than hip hop).

Future enhance­ments will add text to label groups and track names, and bet­ter physics to han­dle col­li­sions and spa­tial overlapping.

Built using Processing and the ProXML library.