A demo introducing my conceptual framework for the computational deconstruction of linear narrative event-space for VR writing and design:
inertial & non-inertial frame
the 2D film frame as multi-dimensional state
cinematic camera perspective designed exclusive of time-based events
camera perspective as multi-dimensional, non-reductive data visualization
Write here...
Here I will continue to organize my ideas pertaining to the thesis I began at ITP.
Use sketchup to experiment with radial arrays of images for developing testing and training data. The physical and visual necessitate human readability and a certain level of design-by-hand.
Create a UML-like language which communicates relational data at high resolution but human-readability. Ponder how language fits into all this - inadequate compared to visual language as a proto-communication protocol between machine and human sight and meaningful association.
50 frames of a radial array in Sketchup. Change line style and different fills on each side of the rectangle surface.
This image represents 50 frames in a radial array. Figure out in Ruby Sketchup API how to fill shape/entity texture/face with unique jpegs representing keyframes from a scene or pages of a screenplay pdf.
clipping from Sketchup shader resolution provides interesting cues about angle of object in orthogonal camera perspective.
two possible camera trajectories over a two-second period.
trajectory lens, radial array
My thesis is about computational analysis design for storytelling.
A use case for the development of a human readable data architecture for parsing film and a sketch for a probabilistic algorithm for teaching it to neural networks.
catherine_Rehwinkel_Thesis =
[{a:['A computational, Bayesian model for film theory',
{b:{‘a use case': 'a conceptual design for a science-fiction universe', {'an android protagonist's: [' embodiment', 'algorithms', 'understanding of human perception of causality through film language and film narrative', {who:('experiences the world as if she is watching a film', 'expresses probabilistic/persuasive courses of action', {to:(human peers, family members)}, {via:('film language', 'narrative structure')})}}}},
{c:{design:{‘a hierarchical data architecture for machine learning to': 'parse film as an n-dimensional film-frame index’}}},
{i:{‘algorithms': {1: 'trains a neural network on director intention and audience reaction'}, {2: 'parses the features correlated with the persuasive success of a film’}}}}];
