The Early Chinese Characters 

Designed Based On The Characteristic Of Everything On Earth

Chinese Legendary Character, Cangjie, Observes Surroundings and Creates Symbols For Everything

1. Machine Intelligence & Experimental Visualization

1.1 Converting Images to Chinese Strokes

we used unsupervised learning techniques to model Chinese character strokes. The learned model is then used to create novel characters based on the images.

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1.2 Training and Using Bidirectional Generative Adversarial Networks (BiGAN)

We trained a neural network (named Cangjie) to learn vector stroke data of over 9000 Chinese characters by using BiGAN. After successfully training, the discriminator and the encoder/generator reach Nash Equilibrium. The network learns a low-dimensional latent representation of these images

• Given an image, the encoder network can produce its latent representation.

• Given the latent representation, the generator network can reconstruct the image.

• The latent vectors follows a normal distribution.

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Intelligent System Demo​

Novel symbols constructed by Chinese strokes are generating in realtime through reconstructing the live streaming using the trained neural network (Cangjie).

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1.3 Experimental Visualization Using Neural Network Generated Image Data

The image data is firstly manipulated with image processing techniques which include image differencing, alpha compositing, filter design, and algorithmic transformation. Then we used OpenGL shading language (GLSL) to relocate the pixels from real-world texture to a position determined by the image generated by Cangjie. The RGBA channels of live streaming will determine the movements. The purpose is to create an ink flow that is consistently writing new symbols that Cangjie generated in realtime by using live streaming texture.

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Visualization Demo​

Cangjie is writing in realtime based on its observation of the real world through a camera. The writing movement is determined by the RGBA channels of live streaming.

2. Spatial Visualization in Virtual Reality Space Using Image Data

1.1 Composition: Algorithmic Virtual World Structure 

Multiple Mathematic algorithms are implemented to create a world structure, including the Voronoi diagram (sparse). 

1.2 Texture Development: Data-Driven Abstract Patterns and Forms

Using different visual languages - arrays of lines, points, curves, photogrammetry point clouds, image data-driven agency, and image processing techniques to compose the virtual world.