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you_me

web appcode;

screen; 13";
2018

 

c o n c e p t

peer-to-peer meditations: stream the digital essence of somebody or something through yourself in real-time

k e y  p r i n c i p l e s

digital spirituality; code as art; machine-learning; alternative web; 

 

p r o c e s s

Users can experience the base64-code from a remote web-camera streaming through their own body.

Try it with two browser windows or two computers/mobiles: Peer to Peer Meditations

All of this runs with webRTC, tensorflow.js and node.js as main parts on the backend: peer.js handles the web-rtc peer connection with a remote peer-server, node.js organizes the automatic connection to a random user in the peer-network, tensorflow.js runs person-segmentation (now renamed to “body-pix) on the local-users webcam - all the canvas-handling and pixel-manipulation is done in javascript.

The result is a meditation experience that reminds of the calming effects of watching static noise on tv screens. As it is peer-based, the users body becomes a vessel for the blueprint and essential idea of something or somebody else. This hopefully creates a sense of connectedness and community while meditating.

While staring at a screen for meditation might not be everyones preferred way of doing it, it is worth exploring this from a futuristic perspective: we probably will be able to stream information directly into our retina, therefore an overlaid, peer-based meditation experience might be worthwhile considering in the future.

c h a l l e n g e s / f u t u r e i m p r o v e m e n t s

At the moment the experience is very one-sided: only one person can see the stream of code flowing through their body, the other one (who provides the image-stream data) gets no explicit notification or visualization that their data gets used as code for the remote partner.

The visuals look very bare, the visual arrangement surrounding the body-silhouette is still relatively arbitrary.

demo

Here a short video-walkthrough streaming video-frames from my mobile phone camera as base64-code through my own silhouette (the latter is picked up by the camera on my laptop and run through a body detection algorithm). All web-based with machine-learning in the browser powered by tensorflow.js and webRTC peer-to-peer streaming (code):