Bubble Vision
“VR is best thought of as the removal of a single human shaped mass from the fabric of the universe. you have the whole universe, and you basically eliminate one human from it. To build a universe in VR, you need to mentally eliminate one single person from her surroundings, which means that this whole universe actually consists of people shaped holes within bubbles.”
How can the gap between human and machine representation become a space for a new kind of drawing?
Here the “viewing” machine, uses filmic techniques to create a dynamic projection installation that subverts conventions of depth. Each of these machines adapts and extends conventions of existing conceptual or mechanical drawings, but elevate them to the level of programmatic and extensible system.
Nausea 360
People have always been fascinated by the ability to record and capture a moment in time for later viewing. Generally, these attempts have been superficial, only capturing a fraction of a scene. With the advent of 360 photography we can now record the entirety of an environment. Devices like Google Cardboard allow us to immerse ourselves in the recording by overtaking our sense of sight. Unfortunately, this augmentation of a single sense can create a feeling of nausea or motion sickness. This nausea occurs when the information collected by our various senses seem to contradict one another. Because 360 are purely observational, i.e. they only track our rotational motion and not our motion through space, this nausea has become an extremely prevalent problem that deters many would-be consumers from taking part.
Nausea 360 is an attempt to quantify and represent the nausea inducing effects of popular 360 videos found on Youtube by tracking the change in velocity and acceleration of the camera in space.
1. Unwrapped 360 Image An example of what the user would see while viewing a 360 video of a person walking through the Louvre with Google Cardboard device.
3. Image Difference
The same frame compared to the next ten consecutive frames.
By calculating the difference between each frame, we get an image where that isolates the intensity and direction of motion represented by white pixels.
5. Derivatives
To be able to compare the motion of one video to another, we take the first derivative to calculate the change in velocity and the second derivative to calculate the change in acceleration.
2. Flattened 360 Image A full 360 degree panorama of an image from the same video flattened to be viewed in its entirety.
4. Average Brightness
Choose an area of the image that only contains no independently moving objects (e.g. walls not people) and take the average brightness.
This results in a metric that allows us to compare the motion between frames in the same video.
6. Visualize
To visualize and exaggerate this motion, we projected the video onto a sphere and mapped its change in velocity to scale and its change in acceleration to vertical motion.
Collaborator: Adam M Pere