Author: Jhave

Word-system

Critters. Fauna. Fibonacci.

A baked shadow render bestiary. Alphabet ecosystem. Cross-referenced between languages. Technically: how many polygons can Unity hold if textures are baked? Will a smaller version play in Yurt if exported in FBX format to VRUI?

Source files available on request.

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Screen Shot 2015-06-25 at 8.52.28 pm Screen Shot 2015-06-25 at 8.47.59 pm

 

So as it is…

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Screen Shot 2015-06-27 at 9.22.52 am Screen Shot 2015-06-27 at 9.21.46 am

 

Clots

Clumps, clots, clouds, flocks, herds, cells, knots
in the blood brain earth sky stars.

In-between the tube videos will be clump videos: these will be easier occasionally technically since each cloud/flock/knot can be isolated on its own screen, no need for synchronized parallel renders unless they cross the edge of a screen.

Prototype Image: O meets E

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In this image a clump of Os meets a clump of Es. Animation occurs by placing a static bend transformer on each cloud, then moving the clouds together through their constraining deformers (instead of changing the deformer, changing the object relevant to its deformer). Ambient occlusion with global illumination and final gather. 220 passes. No default lights. Source file available on request. Screen Shot 2015-06-21 at 9.24.22 pm Screen Shot 2015-06-21 at 9.25.35 pm

Worms made Flesh (tubes)

Organisms are tubes that eat and excrete, inhale and exhale, thinking using neuron paths, absorbing nutrients through gut tunnels. Toothpaste comes in tubes, as does astronaut food. Electricity and water travel through tubes. Languages and digital info travel through fiber-optic tubes between people.

Tubes made of language can therefore be playfully considered as organisms. Worms made flesh.

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Continue reading “Worms made Flesh (tubes)”

Apply erasure technique to the BASIC LAW

Collier and MK will apply erasure techniques to Basic Law Article 1-23 Chapter 1-2 as a first test and give word documents to Leoson.

 

Leoson:

(basic law) technical solution for collier.
capture each chapter/poem as one texture and map in a 3D plane. I split the planes into separate 3D object.

Thus, each word could be animated and each word is treated as one object. like following the curve, more random, dynamic…etc.

The unselected words will be disappeared and and selected words will be animated as in many ways in terms of floating, waving…etc

Fluid Curved 3D Morph Alphabet-Ideogram film

Use emPolygonizer to morph & mutate a short poem.

Begin to learn the software with a set of words based on a mutated great chain of being. Distribute the following words around the cylinder and morph in between the english-cantonese. 5 second loop video. To be placed in-between other poems.

Mineral – Plants – Animals – Humans – Ghosts – Gods – Multiverse
矿物   –    植物   –   动物     –     人类     –      鬼       –  神    –   多元宇宙

Tech Steps

  • I have a single-seat license for previous version of emPolygonizer . Upgrade and install on Toshiba.
  • Produce simple film as a test using “Mineral – Plants – Animals – Humans – Ghosts – Gods – Multiverse 矿物 – 植物 – 动物 – 人类 – 鬼 – 神 – 多元宇宙”
  • Experiment with interactive jumps in film: is it smooth… etc…
  • See https://vimeo.com/89911203

Image-Text Test Mashup (tumblrs & twitters)

Use appropriated images (from http://jhave.tumblr.com/ ) to form stacked trptychs with Cantonese and English words in gaps between the images (see https://ello.co/jhave2 for examples and sample phrases) .

Same technique for remixing the images and words from http://jhavehk.tumblr.com/ Example : healer image uses title of photo beneath it. Stanzas could go on either side.

Similar technique for words from https://twitter.com/jhave2 .  Note: tweets since November 2014 are stored here in a doc file that automatically appends recent tweets. No images needed. Professional translation required.

 

Tech Steps:

  • Use some sort of automated extraction to download all of these sites.
  • Use batch auto-translate to perform rough english-to-cantonese
  • Dynamic load images
  • Dynamic resize
  • Simple animation slides
  • Dynamic text
  • Randomize load but empty array (see every image and every text before repeat)
  • Interactive trigger to shuffle image-text
  • Add soundtrack from https://glia.bandcamp.com/ (experiment in consultation with Jhave)
  • Long-range goal (Jhave + Leoson todo together) : run machine-learning python script to extract patterns in text ( see http://bdp.glia.ca/t-sne-classification-of-10557-poems/ ) and a similar script to analyze images. Then dynamic load based on proximity.