CHAPTER 2
EXPERIMENT 2.1
Concept: Exploring visual personalization by converting input images into dithered visuals. Simplifies high-resolution data into limited colors and blocks.
Error Codes: These patterns show what happens when the system uses bad data. The blocks show how unstable input turns into unique visual textures.
Noise Exploration: Explored Perlin noise and fractal noise. However, standard noise generators were deemed too predictable and bland for the project's aesthetic needs.
Process: Tested how Blender handles input variables like rotation, speed, or scale to output visuals using Python scripts.
Technical: Scripts control positioning, color, and geometry of clustered objects, establishing a robust foundation for external sensor data.
Aesthetic: Designed scalable, abstract visuals that can be customized for any user's personal style.
EXPERIMENT 2.2
EXPERIMENT 2.3
Process: Using NFC tags as physical tokens to switch visual modes instantly.
Technical Setup: Used a multiplexer (MUX) to handle three NFC readers on a single set of pins, simulating six unique input choices.
Proposed Prototype: Placing a physical token on the designated surface would instantly load a unique visual scene, allowing for rapid aesthetic switching.