Sterling Crispin uses evolutionary algorithms to produce masks that satisfy facial recognition algorithms: "my goal is to show the machine what it’s looking for, to hold a mirror up to the all-seeing eye of the digital-panopticon we live in and let it stare back into its own mind."
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In Xerox scanners/photocopiers randomly alter numbers in scanned documents, computer scientist David Kriesel shows that the Xerox WorkCentre 7535 randomly changes the numbers in its scans. The copier has firmware that tries to compress images by recognizing the numbers and letters in the documents it scans, and when it misinterprets those numbers, it produces untrustworthy output. The bug also occurs in the Xerox 7556 and possibly other machines, and as Kriesel points out, this could mean that engineering diagrams, invoices, prescriptions, architectural drawings and other documents whose numeric values are potentially a matter of life-and-death (or at least financial stability) are being randomly edited by machines we count on to produce faithful copies.
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Fast, Accurate Detection of 100,000 Object Classes on a Single Machine a prizewinning paper by Google Research scientists, describes a breakthrough in machine vision that can distinguish between a huge class of objects 20,000 times faster than before.
This so-called convolution operator is one of the key operations used in computer vision and, more broadly, all of signal processing. Unfortunately, it is computationally expensive and hence researchers use it sparingly or employ exotic SIMD hardware like GPUs and FPGAs to mitigate the computational cost. We turn things on their head by showing how one can use fast table lookup — a method called hashing — to trade time for space, replacing the computationally-expensive inner loop of the convolution operator — a sequence of multiplications and additions — required for performing millions of convolutions with a single table lookup.
We demonstrate the advantages of our approach by scaling object detection from the current state of the art involving several hundred or at most a few thousand of object categories to 100,000 categories requiring what would amount to more than a million convolutions. Moreover, our demonstration was carried out on a single commodity computer requiring only a few seconds for each image. The basic technology is used in several pieces of Google infrastructure and can be applied to problems outside of computer vision such as auditory signal processing.
Fast, Accurate Detection of 100,000 Object Classes on a Single Machine
(Image: Clutter, a Creative Commons Attribution Share-Alike (2.0) image from neofob's photostream)
Martin Backes is selling a limited edition of 333 "Pixelhead" anonymity masks, which allow you to replace your face with the pixellated likeness of German Secretary of the Interior Hans-Peter Friedrich. Masks are made to order and to measure, take 4-6 weeks for delivery, and cost €158 with shipping.
The full face mask Pixelhead acts as media camouflage, completely shielding the head to ensure that your face is not recognizable on photographs taken in public places without securing permission. A simple piece of fabric creates a little piece of anonymity for the Internet age. The material used is elastic fabric for beach fashion and sports gear with a fashionable Pixel-style print of German Secretary of the Interior Hans-Peter Friedrich. The mask has holes for your eyes and mouth, so you can see and breathe comfortably while wearing the mask, secure in the knowledge that your image won’t be showing up anywhere you don’t want it to.
Pixelhead Limited Edition
Timo's video "Robot readable world" is made up of stitched-together found footage from computer vision systems, "exploring the aesthetics of the robot eye." It was inspired by Matt Jones's essay The Robot-Readable World, and it reminds me Laura Mulvey's idea of the Male Gaze.
Robot readable world