@SelfiesBot: It’s Alive!!!

@SelfiesBot began tweeting last week and already the results have surprised me.

Selfies Bot is a portable sculpture which takes selfies and then tweets the images. With custom electronics and a long arm that holds a camera that points at itself, it is a portable art object that can travel to parks, the beach and to different cities.

I quickly learned that people want to pose with it, even in my early versions with a cardboard head (used to prove that the software works).

Last week, in an evening of experimentation, I added text component, where each Twitter pic gets accompanied by text that I scrape from Tweets with the #selfie hashtag.

This produces delightful results, like spinning a roulette wheel: you don’t know what the text will be until the Twitter website pubishes the tweet. The text + image gives an entirely new dimension to the project. The textual element acts as a mirror into the phenomenon of the self-portrait, reflecting the larger culture of the #selfie.

Produced while an artist-in-residence at Autodesk.

aaron
mikkela

And this is the final version! Just done.

selfes_bot_very_good

This is the “robot hand” that holds the camera on a 2-foot long gooseneck arm.

robot_hand
yo

two_people

martin

 

World Data Crystals

I just finished three more Data Crystals, produced during my residency at Autodesk. This set of three are data visualizations of world datasets.

This first one captures all the population of cities in the world. After some internet sleuthing, I found a comprehensive .csv file of all of the cities by lat/long and their population and I worked on mapping the 30,000 or so data points into 3D space.

I rewrote my Data Crystal Generation program to translate the lat/long values into a sphere of world data points. I had to rotate the cubes to make them appear tangential to the globe. This forced me to re-learn high school trig functions, argh!

world_dcWhat I like about the way this looks is that the negative space invites the viewer into the 3D mapping. The Sahara Desert is empty, just like the Atlantic Ocean. Italy has no negative space. There are no national boundaries or geographical features, just cubes and cities.

I sized each city by area, so that the bigger cities are represented as larger cubes. Here is the largest city in the world, Tokyo

world_tokyo

This is the clustering algorithm in action. Running it realtime in Processing takes several hours. This is what the video would look like if I were using C++ instead of Java.

I’m happy with the clustered Data Crystal. The hole in the middle of it is result of the gap in data created by the Pacific Ocean.

world_pop_crystal

The next Data Crystal maps of all of the world airports. I learned that the United States has about 20,000 airports. Most of these are small, unpaved runways. I still don’t know why.

Here is a closeup of the US, askew with Florida in the upper-left corner.

us_closeup

I performed similar clustering functions and ended up with this Data Crystal, which vaguely resembles an airplane.

world_airports_data_crystalThe last dataset, which is not pictured because my camera ran out of batteries and my charger was at home represents all of the nuclear detonations in the world.

I’ll have better pictures of these crystals in the next week or so. Stay tuned.