The impetus behind the Pulsefield is rooted in creating interactive environments that encourage emergent group behavior. What happens when a group of strangers start interacting in an environment which responds to their movements in ways that reward their cooperation? Do people play independently or do they coordinate their actions to create more rewarding outputs?
The apps in the Pulsefield are designed to provide immediate feedback to participants to create an interesting interaction, but also reward group behavior. For example, in the Guitar app, participants quickly realize that their movements fret and strum notes on a virtual guitar. However, the results are independent, uncoordinated notes. Strangers in the Pulsefield who have been given no instruction in its use figure out how to make sounds, and more importantly, begin to self-organize. Invariably, one of the participants (usually one who plays guitar), will take control and get everyone to coordinate their position to start playing simple chords. They will then progress, sometimes more successfully than others, to play out simple melodies. Within a few minutes of entering you have a group of people working together.
The Pulsefield is also an experiment in creating an open platform for further exploration. By creating a loosely-coupled architecture between the basic tracking, video, sound, and light generation, the system allows collaboration and development of multiple Apps that can operate on the Pulsefield. These can be experiments in music synthesis, generative video, social interaction, or simply multi-player physical games.
From a technical point of view, the goal was to build a system that can track people with the following specifications:
- Resolution of 1-2 cm over the entire space of >300 square meters.
- Ability to track up to 20 people simultaneously.
- Updates at 10-20 frames/second
- Less than 100ms (preferably 50ms) latency
- Robust in changing lighting conditions (including operating in full sunlight or at night)
These parameters were chosen to allow the device to be played like a musical instrument with ability to detect small movements accurately and reliably. Existing tracking methods such as overhead cameras using computer vision algorithms or infrared sensors are not able to provide this level of performance over the large space. The Pulsefield implementation is able to achieve these objectives and should be able to cover even larger areas with minimal changes.