maps & mulch

Hello I'm Max, a cartographer living in Berlin. browse submit ask blip.fm - facebook - twitter

[forthegifted]

[mxfh]

(via forthegifted)

Legendary.

[prostheticknowledge]

Dwitter

Social Network by Andreas Løve Selvik for Javascript computer graphics coding presents visual experiments in 140 characters or fewer, and all run slick in-browser.

See for yourself here

[mxfh]

Oh; apparently I've been busy elsewhere in my years off tumblr.

[natgeofound]

Alexander Graham Bell and Mabel kissing within a tetrahedral kite, October 1903. Photograph courtesy Library of Congress

[mxfh]

London Bridge is a brisk twenty-five minute walk from my flat. Last night, I heard the sirens. By the time the news began to arrive in fragments, the notifications started on my Facebook page, letting me know that “so-and-so has marked themselves safe on Facebook”.

"We’d be better off checking in as ‘safe’ after our morning commute"

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Caspian Sea Monster's neighborhood just isn't the same anymore.

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There are few things more dangerous than an overconfident point when it’s placed on a map.

Missing the Point- GeoIP's, Points, Polygons, and a Precarious Farm in Kansas · Mapzen

[prostheticknowledge]

Neural Image Analogies and Neural Doodles

Computer Science research from Adam Wentz and Alex Champandard (coincidentally, not together) extends neural network style transfer method allowing to dictate how image sections should be stylisticly composed and rendered (in two different ways).

The initial concept was put together by MRL NYU in 2001, and here is a demostration video to highlight the concept:

We present a new framework for processing images by example, called “image analogies.”  Rather than attempting to program individual filters by hand, we attempt to automatically learn filters from training data.

… our system “learns” the transformation from A to A’, and then applies that transformation to B to get B’.  In other words, we compute B’ to complete the analogy.

More Here

Then Adam Wentz has updated the work to faciliate contemporary developments and technology:

This is basically an implementation of this “Image Analogies” paper http://www.mrl.nyu.edu/projects/image-analogies/index.html In our case, we use feature maps from VGG16. The patch matching and blending is done with a method described in “Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis” http://arxiv.org/abs/1601.04589  Effects similar to that paper can be achieved by turning off the analogy loss (or leave it on!) and turning on the B/B’ content weighting via the --b-content-w parameter.

The Abe Lincoln image above was put together by Audun Mathias Øygard using Adam’s work.

Code can be found here

Alex Champandard has also developed his own code and paper in this field which he calls ‘Neural Doodles’:

Convolutional neural networks (CNNs) have proven highly effective at image synthesis and style transfer. For most users, however, using them as tools can be a challenging task due to their unpredictable behavior that goes against common intuitions. This paper introduces a novel concept to augment such generative architectures with semantic annotations, either by manually authoring pixel labels or using existing solutions for semantic segmentation. The result is a content-aware generative algorithm that offers meaningful control over the outcome.  Thus, we increase the quality of images generated by avoiding common glitches, make the results look significantly more plausible, and extend the functional range of these algorithms—whether for portraits or landscapes, etc.  Applications include semantic style transfer and turning doodles with few colors into masterful paintings!

His research paper can be found here

[tomwhitwell]

One of my favourite techniques… involves searching the default file formats for digital cameras plus four random numbers. This dredges up videos so unwanted that they were never named. In some cases, not even the person who filmed the videos seems to have watched them.

How ‘The Dress’ exposes viral media’s shaky future | Fusion (via tomwhitwell)

[ilovecharts]

Comparison of bands name checked in the LCD soundsystem song “Loosing My Edge” with those name checked in Pitchfork’s song-by-song LCD soundsystem retrospective.

[prostheticknowledge]

Protopiper

Fabrication prototyping tech from the HPI Human Computer Interaction Lab is a computerized tapegun that can produce 3D forms to help visualize objects in spaces:

Protopiper is a computer aided, hand-held fabrication device that allows users to sketch room-sized objects at actual scale. The key idea behind protopiper is that it forms adhesive tape into tubes as its main building material, rather than extruded plastic or photopolymer lines. Since the resulting tubes are hollow they offer excellent strength-to-weight ratio, thus scale well to large structures. 

More Here and Here

[atlasofprejudice]

Culinary Map of Europe According to Italy, from Yanko Tsvetkov’s Atlas of Prejudice: The Complete Stereotype Collection, available on a paperback from Amazon and as an ebook on iBooks.

[mxfh]

http://cdn1.tnwcdn.com/wp-content/blogs.dir/1/files/2015/09/fn63697_03.jpg

(via This hilarious Cisco fail is a network engineer's worst nightmare)

The side view looks even more perfect.

[mxfh]

(via まっつぁん︎ on Twitter: "ピタゴラスイッチの今日のスレスレが進化してて気持ち良さ倍増している http://t.co/NmHffFsloJ")

[new-aesthetic]

[mxfh]

New Boss on Construction Sites Is a Drone | MIT Technology Review

For some construction workers, any thoughts of slacking off could soon seem rather quaint. The drones will almost certainly notice.

The workers building a lavish new downtown stadium for the Sacramento Kings in California are being monitored by drones and software that can automatically flag slow progress.

Once per day, several drones automatically patrol the Sacramento work site, collecting video footage. That footage is then converted into a three-dimensional picture of the site, which is fed into software that compares it to computerized architectural plans as well as a the construction work plan showing when each element should be finished. The software can show managers how the project is progressing, and can automatically highlight parts that may be falling behind schedule.

Such additional scrutiny is controversial. It raises worries over worker privacy, for instance, and fears that people may be encouraged to work excessive hours.

Golparvar-Fard concedes that this could be an issue, but he defends the idea. “It’s not new to the construction industry that there would either be people standing and observing operations, or that there would be fixed cameras,” he says. “Yes, making this autonomous has a different feeling for the workers. But you have to keep in mind that it’s not really questioning the efficiency of the workers, it’s questioning what resources these guys need to be more efficient.”

[prostheticknowledge]

Sampling Based Scene-Space Video Processing 

Paper from Disney Research explores various visual effects which can be employed in video recording using a 3D depth camera:

Many compelling video processing effects can be achieved if per-pixel depth information and 3D camera calibrations are known. However, the success of such methods is highly dependent on the accuracy of this “scene-space” information. We present a novel, sampling-based framework for processing video that enables high-quality scene-space video effects in the presence of inevitable errors in depth and camera pose estimation …

… Our generic scene-space formulation is able to comprehensively describe a multitude of video processing applications such as denoising, deblurring, super resolution, object removal, computational shutter functions, and other scene-space camera effects. We present results for various casually captured, hand-held, moving, compressed, monocular videos depicting challenging scenes recorded in uncontrolled environments.

There currently is no embeddable video at time of posting, but a video you can watch can be found here

You can find out more about the work at Disney Research here

[Post updated 7 August 2015 with embedded video]

[mxfh]

Extracted depth information enabling Virtual Aperture and Lens Effects has to be the new instagram filter for video soon. The spatio-temporal future looks bright.

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(via Science Graphic of the Week: Monitoring Ocean Waves From Space | WIRED)

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(via The Housing Value of Every County in the U.S. | Metrocosm)