social sqncr is an interactive audio-visual installation that aims to make people more aware of the act of creating their public identity.

To create their ‘identity’, participants use their bodies to physically interact with a pseudo-musical instrument projected in a physical space to create virtual musical creatures based on their movements. The instrument consists of eight zones that participants interact with which influence the shape, movement, and aural properties of the resulting entity.

Once complete, the system captures an image of the participant to attach to the creature which is then set free into an eco-system inhabited by similar entities. The entities react to one another, much like human beings in a social network. Participants can cause environmental disturbances by physically interacting with the projection.

The physical movements required of participants ensures a high level of investment in the process, causing a heightened awareness of their creation, and thus themselves. Watching their entity interact with other entities is a reflection of their own interaction in their social networks.

SOCIAL SQNCR WEBSITE

Click here to view the embedded video.

ShredBoard is an instrument that usees the conventional keyboard and mouse as input. The keys z-/, a-’, q-] and 1-= are mapped to the notes of four guitar strings starting at E, A, D, G for each row of keys. The mouse is mapped to be used as an effect pedal. There are 2 effects – one that is sort of clean and the second which is distorted. Parameters can be adjust with 3 knobs to produce different tones.

The software is written in AS3 and exported as an AIR application. The sounds are produced in SuperCollider by sending OSC messages via flosc. I had to hack the flosc AS3 classes to send the desired messages to SuperCollider.

Files:

• AIR Application
• shredboard source
• SuperCollider file
• You’ll need to install SuperCollider and flosc before running this application.

Social Creatures

Nick Hardeman and Bruce Drummond, 03.23.10.

Social Creatures is an interactive audio-visual installation that aims to make users more aware of the act of creating their public identity. To create their ‘identity’, people use gestures to select a particular form and then interact with a pseudo-musical instrument. The instrument consists of eight visual zones that influence the shape and aural properties of the resulting entity. Once complete, users can name the entity using a mobile device, and then set it free into an eco-system inhabited by similar entities. In the eco-system, the entities react to one another, much like human beings in a social network. Users can use a mobile device to command various entities or cause environmental disturbances through simple gestures.

The physical gestures required of the users ensures a higher level of investment in the process, causing a heightened awareness of one’s creation, and thus oneself. Watching the entity interact with other entities is a reflection of our own interaction in our social networks.

Latest technical prototype, concept statement, look and feel prototype and interaction model for thesis.

Midterm Presentation:

Ars Electronica 2007 Live performance.

Weather Tube Report displays the weather condition and a selection of videos from YouTube, based on the zip code you enter. The videos are selected on the fly based on predetermined search parameters. The weather condition dictates these parameters – which include musical styles and instruments – to search for suitable videos. The weather condition also determines the background color.

The name is inspired by the band Weather Report and some of their song names are used to produce the gibberish text to display the temperature and condition.

Weather Tube Report uses the Yahoo! Weather API to retrieve weather information, the YouTube API to retrieve videos and a database to store the search parameters.

Built with PHP, MySQL, HTML, CSS and jQuery.

Check it out here!

Feel free to leave me comments, questions, feedback, bug reports below. Enjoy!!

Check it out!

A visualizer for Leo’s Room by Vangelis, from the movie Blade Runner. The visualizer was made with C++/OpenFrameworks and composited into a single still image. I created this as the first assignment for the Visual Music Studio class at Parsons.

Quikdrawl is a drawing interface which uses 2 hacked gun game controllers with red LED attached to the front of each. Clicking the trigger turned on the LED which was color tracked to find it’s location. Each time the trigger is pressed, a bullet hole through layered textures appears on the screen. The textures were preprepared but the intention is that these would be captured and created from a certain section of the users silhouette and layered in with previous textures. Nick, Steve and me worked on this application for our set pixel class. Made with OpenFrameworks.

A scene for the a/v engine/live performance visualization tool Nick, Steve and me are working on. This is an underwater scene where bubbles are generated based on the FFT and emerge from the near the top of the cv blob, near the performers mouth. The bubbles generated in the background are also based on the FFT and bounce of off of the performers contour. These are produced to give the illusion of swimming through water to the top. The screen capture is a little laggy and has a test video overlayed to demonstrate the position of the performer. The scenes were created with the intention of performing live with Analogue Transit. Music in these videos by: Nine Inch Nails

TweetCatcha seeks to uncover the organic nature of news as it travels through Twitter over time, by examining the movement of NY Times articles through Twitter. Nick and me worked on this project for our data visualization class and my AS3 class.

The New York Times Newswire API is used to load news for the last 24 hours. The title and URL for the retrieved articles are used to search for tweets with the BackTweets API, a BackType service.

The articles are placed around the center arranged clockwise based on the time they were published. The tweets for each article emanate from the article near the center to the outside. These are based on the time difference between when the article was published and when it was tweeted. The 24 rings indicate the hour difference from 1 near the center to 24 near the outside.

Data was collected between November 13, 2009 and February 9, 2010 via a cron job set up to pull and store the data locally. The current database is 107 MB, with 15,327 NYTimes articles and 311,885 tweets for those articles.

Demo

Presentation: