View allAll Photos Tagged voronoi
Sample renders for sculpture. What do you think I should cut it from - wood or plastic? Or maybe cardboard?
@ SLEA6 maps.secondlife.com/secondlife/SLEA6/250/4/21
From July till December 2021.
Several Levels of installations.
Follow TP menu at LM
Lace Hill in Yerevan, Armenia by Forrest Fulton Architecture for International Business Center competition
forrestfulton.com/lace-hill-over-yerevan
Lace Hill stitches the adjacent city and landscape together to support a holistic, ultra-green lifestyle, somewhere between rural hillside living and dense cultured urbanity. The 85,000 square meter (900,000 sf) proposal is a new model of development for Yerevan and Armenia that supports a resilient, high-value spatial fabric, dense with overlapping natural and urban phenomenon.
a test piece from a new working theory of pleating.
polygons are defined by the same methodology used to make Voronoi tessellations; borders are then used as a reference crease along with the central point of the polygon to create the appropriate "fold flat" crease pattern. in this case, you can see the original 1/2 pleat creasings, which were further divided into 1/4 width pleats.
This was a test using random polygons; other methods of more usefulness (applications for use with regular polygonal shapes) are in development.
much fruit on this tree, I think. I hope I am able to refine my ideas enough to make them usable.
if you find this idea interesting at all, please drop me a line at origomi [ at ] mac.com. I'd be happy to talk to you about it.
Testing my new medial-surface (a sort of 3D-Voronoi) grasshopper definition on a trefoil knot. More to follow shortly at:
Another batch of photos I never got around to uploading.
In June 2013 there was a lighting conference that happened in Wellington which had tons of public lighting sculptures.
my latest "crime against cartography".
This monstrosity is a voronoi network from the world's airports, courtesy of OpenFlights (basically, each tile represents one airport, and all the points on the earth that are closest to that airport). The smaller the tiles, the more densely clustered the airports are.
They were coloured in in QGIS using the shapeburst fill and a suitably bad choice of colour gradient. This may be slightly less painful to view if you're colourblind.
London Broad Street cholera outbreak (1854)
Data:
+ Openstreetmap, Stamen Design
+ Cholera Map (PD)
+ Thiessen/Voronoi Polygons
using QGIS, Python and Postgres/PostGIS.
Inspired by this question on GIS Stack Exchange about world building. Using QGIS / Python / PostGRES / PostGIS to create a random world.
Starting with a voronoi lattice, used a flood-fill algorithm to make each city spread outwards into uncontested neighbouring areas.
Cells adapt automatically to user's drawn table contour and chosen height as well as CNC-bending machine constraints. Structural integrity of evolved object is ensured via FEM feedback.
Executed at Lund University School of Industrial Design by Andreas Hopf and Axel Nordin, supported by Vinnova, Sweden.
andreas.hopf@design.lth.se
axel.nordin@mkon.lth.se
The artworks are created with high-resolution (from 50 megapixel) with lots of details. If you are interested in any way to buy artworks or you just want some additional info, contact me: jc2046 [-at-] gmail.com
laserdelic.com
A voronoi treemap of the primates, based on the Tree of Life dataset. Each polygon represents a species, with border thickness and color attempting to show cladistic groupings. The right side is Strepsirrhini (lemurs, galagos, lorises), the right one has tarsiers in mint at the top, new world monkeys in purple, the old world monkeys in dark blue, hominids in light blue and gibbons in green.
H sapiens is the heart-shaped sky-blue polygon, surrounded by our extinct relatives and with chimps in the left corner, orangutans at the top and gorillas at the bottom corner.
The visualisation clearly has some way to go before being ready for prime time, but it is already appealing.
The image was calculated in Matlab. I used a variant of Balzer & Deussen's algorithm without the messy sample points and polygon extraction parts; I have to pay in terms of polygon quality instead, but I think I can fix that.
Why?
Locality is inherent to the value of craigslist; I go to craigslist.org but I get kicked over to the local instance of craigslist (my IP address sources me to somewhere in the illustrious Lansing, MI). But how does craigslist know where to send me? Some mysterious system of assigning a geocoded IP address to just the right site must be in place...I wonder what that map looks like.
When Ian Clemens proposed the idea, I looked around to find an existing map of craigslist sites-to-areas -maybe even find the lookup that they themselves use. I couldn't find anything like it.
Whether it matches their system well or not, here is a map that approximates geographic coverage to individual sites using a Voronoi process as a base (more info on process below). It is at least a start at visualizing the geographic coverage and distribution of the community-driven instances of craigslist. Shapes like this might provide some useful context for other data, demographic or market information, for instance. Also, when pulled into VFX, it can serve as an input to some spatial querying on those other metrics.
This and other ginormous map prints available at www.zazzle.com/idvswag
ref: www.fontplay.com/freephotos/fifthn/fp051306-25.jpg
Using a plugin called Mosaic Tile Helper (GIMP) and then stroking the dots makes for a much cleaner mosaic then Voronoi Stippler, imo. :)
Architect: Minifie Nixon_Centre for Ideas. The generative process used in the VCA Centre for Ideas is an expansion from an algorithm for establishing the voronoi tessellation of a plane. Architect: Fender Katsalidis_Buxton Contemporary Gallery
The Mammals, displayed using a further development of my Voronoi treemap code (now with nicer borders and more robust calculations). Each polygon represents a mammalian species or group of species, distributed inside larger groupings.
I love it when other folks riff on things you've worked on.
These images are by @Unpixelled on the Digital LEGO Designers Community Discord. Unpixelled had the original idea for a kintsugi custom material. I helped figure out how to use the Voronoi node to create the cracks. Then Unpixelled took over again to create this amazing Stone + Kintsugi custom material.
The other thing I love is when LEGO becomes the jumping off point for other artistic approaches. You'll never get this with real LEGO pieces, but virtually...you can go anywhere your imagination takes you. So cool...so cool!
playing around with the Mesh library voronoi regions workshop.evolutionzone.com/2008/06/01/mesh-library-demo/
I rendered this image in Blender (a free 3D modelling, rendering, animation, and game engine program from www.blender.org). I'm still learning Blender so it was a learning process for me.
It was a straightforward process: I just added "Text", adjusted the "Extrude" setting, applied a Bevel Depth and BevResol, then added a Gold Voronoi material texture. (The material I found on the Blender Open Material Repository.) Although, I did adjust the material settings slightly to make the texture more coarse and "bumpy".
This is licensed under CC BY 2.0, so you may use it in whatever project as long as the license is followed. Basically, just give me some credit and, when possible, link to this page.
CC. Some rights reserved.
Golden_Dollar_Sign by Benjamin Sperandio is licensed under a Attribution 2.0 Generic (CC BY 2.0) License.
I'm obsessed with networks, links and relationships. Links across time and space but specially the ones we create as social beings: Parenthood, love, friendship.
How can I reflect in a visual piece the deep relationship with my family? my answer is to transform photographs in networks of lines and points, employing Processing to build Voronoi graphs based in the difference in brightness intrinsical to each image.
Then I create "maps" juxtaposing side by side the voronoi graphs and build a network, a set of pathways that relate one with each other in an "organic" way.
I'm not a programmer, I'm sure a person with the patience and the knowledge will create something more spectacular or complex. But for me, at this moment, this simple network is an interesting way of show what lies below most of my photographic work.
Thanks for your time. I you can plese visit my Portfolio of photography or my Facebook page.
Despite its association with Boston, "wicked" (blue) is also dominant over "hella" (red) in the United Kingdom, the Netherlands, and Canada. "Gnarly" (green) is rare everywhere.
This probably really ought to have a base map.
Data from the Twitter streaming API through November 30, 2011.
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TABLE LAMP XX BUTTERFLY
Nature and math is an ocen of inspiration. The organic pattern contains three structures (plus butterflies main lines) and each of them is based upon Voronoi diagram – one of those mathematical oddities (like fractals) that turns up frequently in the world of nature.
The head of the lamp is made of Senegalese gourd. Its diameters are 27 and 23cm.
Thickness of the gourd is about 1cm so the structure is quite deep and it is carved on three different depth levels.
Height of the whole lamp is 48cm.
The diameter of the base is 28cm and it is finished with dark brown jeweler waxed string.
The end of the base is carved from wood.
On the top of the lamp is closing part locked with little magnets.
Trying out my new Nikon 60mm macro lens. The depth of field is much more manageable than my home-brew reversal macro lens. This should give me more flexiblity and control when composing shots.
Did a final day of testing to find an ideal bubble mixture liquid medium which would stand up to the ferrofluid being drawn through the capillaries.
Twitter: twitter.com/#!/kpimmel
QGIS 2.18.10, using data copyright OpenStreetMap contributors. Uses data from NaturalEarth data (hypsometric tint and state boundaries).
Inspired by the look of National Geographic maps. 13 layers in total :-)
No manual label placement was used.
Used a combination of weights, z-orders and default cartographic label placement.
To reduce clutter in dense areas, I used a voronoi mesh and only rendered smaller towns whose voronoi cell was greater than a certain area (200 km^2). This means only towns with a large enough 'catchment area' get shown.
Next challenge: create densified lines in the target CRS, so the state names curve nicely with the grid...