Emergency Typography

Timestamp: 1413741900

Emergency Typography

p5art:

So I finally gave that introductory creative coding workshop. For what it’s worth, here’s the PowerPoint presentation (190 MB! because of videos) I made to show people what creative coding is about. I tried to represent the whole spectrum (as far as I’m aware of it). Sorry for those of you doing really cool stuff that I forgot to include …… 

Learn to make GIFs like this!

Timestamp: 1413656679

p5art:

So I finally gave that introductory creative coding workshop. For what it’s worth, here’s the PowerPoint presentation (190 MB! because of videos) I made to show people what creative coding is about. I tried to represent the whole spectrum (as far as I’m aware of it). Sorry for those of you doing really cool stuff that I forgot to include …… 

Learn to make GIFs like this!

escapekit:

The Gif Connoisseur

famed illustrator Norman Rockwell painted The Connoisseur for The Saturday Evening Postmagazine. It shows a man standing in front of a Jackson Pollock-esque style painting at a museum or gallery. Today, that same character, in his matching suit, is back to see a more modern form of art known as the animated GIF.

Check out the rest of the work here

(Source: mymodernmet.com, via darksilenceinsuburbia)

Timestamp: 1413400998

escapekit:

The Gif Connoisseur

famed illustrator Norman Rockwell painted The Connoisseur for The Saturday Evening Postmagazine. It shows a man standing in front of a Jackson Pollock-esque style painting at a museum or gallery. Today, that same character, in his matching suit, is back to see a more modern form of art known as the animated GIF.

Check out the rest of the work here

(Source: mymodernmet.com, via darksilenceinsuburbia)

edunez:

"Witch Hunt" - Caza de Brujas - nez 2014. 

#gifart #gif

Timestamp: 1413400419

edunez:

"Witch Hunt" - Caza de Brujas - nez 2014. 

#gifart #gif

prostheticknowledge:

MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction

Interesting development for 3D video: a team at Carnegie Mellon University have developed a method of video photogrammetry to capture 3D motion, using a spherical array of video cameras at various angles within a space entitled ‘The Panoptic Studio’ - video embedded below:

Many traditional challenges in reconstructing 3D motion, such as matching across wide baselines and handling occlusion, reduce in significance as the number of unique viewpoints increases. However, to obtain this benefit, a new challenge arises: estimating precisely which cameras observe which points at each instant in time. We present a maximum a posteriori (MAP) estimate of the time-varying visibility of the target points to reconstruct the 3D motion of an event from a large number of cameras. Our algorithm takes, as input, camera poses and image sequences, and outputs the time-varying set of the cameras in which a target patch is visible and its reconstructed trajectory. We model visibility estimation as a MAP estimate by incorporating various cues including photometric consistency, motion consistency, and geometric consistency, in conjunction with a prior that rewards consistent visibilities in proximal cameras. An optimal estimate of visibility is obtained by finding the minimum cut of a capacitated graph over cameras. We demonstrate that our method estimates visibility with greater accuracy, and increases tracking performance producing longer trajectories, at more locations, and at higher accuracies than methods that ignore visibility or use photometric consistency alone.

More Here

(via notational)

Timestamp: 1413247844

prostheticknowledge:

MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction

Interesting development for 3D video: a team at Carnegie Mellon University have developed a method of video photogrammetry to capture 3D motion, using a spherical array of video cameras at various angles within a space entitled ‘The Panoptic Studio’ - video embedded below:

Many traditional challenges in reconstructing 3D motion, such as matching across wide baselines and handling occlusion, reduce in significance as the number of unique viewpoints increases. However, to obtain this benefit, a new challenge arises: estimating precisely which cameras observe which points at each instant in time. We present a maximum a posteriori (MAP) estimate of the time-varying visibility of the target points to reconstruct the 3D motion of an event from a large number of cameras. Our algorithm takes, as input, camera poses and image sequences, and outputs the time-varying set of the cameras in which a target patch is visible and its reconstructed trajectory. We model visibility estimation as a MAP estimate by incorporating various cues including photometric consistency, motion consistency, and geometric consistency, in conjunction with a prior that rewards consistent visibilities in proximal cameras. An optimal estimate of visibility is obtained by finding the minimum cut of a capacitated graph over cameras. We demonstrate that our method estimates visibility with greater accuracy, and increases tracking performance producing longer trajectories, at more locations, and at higher accuracies than methods that ignore visibility or use photometric consistency alone.

More Here

(via notational)

ludonaut:

Playing with Nico Disseldorp’s Tesselation Kit, or as I like to call it: Accidental Swastika Creator.

The color schemes are supposedly random, but holy tapdancing hexagon, they’re all beautiful.

(via johnjohnston)

Timestamp: 1412700065

ludonaut:

Playing with Nico Disseldorp’s Tesselation Kit, or as I like to call it: Accidental Swastika Creator.

The color schemes are supposedly random, but holy tapdancing hexagon, they’re all beautiful.

(via johnjohnston)

1982 TRON Beach Towel, $7.95 with two Dial or Tone proofs-of-purchase.

Timestamp: 1412694240

1982 TRON Beach Towel, $7.95 with two Dial or Tone proofs-of-purchase.

One of those can’t-get-it-together-days.

Timestamp: 1412693040

One of those can’t-get-it-together-days.

Timestamp: 1412692975