Circumvent Facial Recognition With Yarn

Knitwear can protect you from a winter chill, but what if it could keep you safe from the prying eyes of Big Brother as well? [Ottilia Westerlund] decided to put her knitting skills to the test for this anti-surveillance sweater.

[Westerlund] explains that “yarn is a programable material” containing FOR loops and other similar programming concepts transmitted as knitting patterns. In the video (after the break) she also explores the history of knitting in espionage using steganography embedded in socks and other knitwear to pass intelligence in unobtrusive ways. This lead to the restriction of shipping handmade knit goods in WWII by the UK government.

Back in the modern day, [Westerlund] took the Hyperface pattern developed by the Adam Harvey and turned it into a knitting pattern. Designed to circumvent detection by Viola-Jones based facial detection systems, the pattern presents a computer vision system with a number of “faces” to distract it from covered human faces in an image. While the knitted jumper (sweater for us Americans) can confuse certain face detection systems, [Westerlund] crushes our hope of a fuzzy revolution by saying that it is unsuccessful against the increasingly prevalent neural network-based facial detection systems creeping on our day-to-day activities.

The knitting pattern is available if you want to try your hands at it, but [Westerlund] warns it’s a bit of a pain to actually implement. If you want to try knitting and tech mashup, check out this knitting clock or this software to turn 3D models into knitting patterns.

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Four images in one. Top left is an image of four individuals in a room with whiteboards and desks in the background along with various clutter on the floor. Over the people is a wireframe overlay of their poses. The image on the top right is just the wireframe people on a black background. Bottom left image is of a single individual standing in a room with the pose wireframe overlay. Bottom right image is the single pose wireframe on a black background.

Tracking Humans With WiFi

In case you thought that cameras, LiDAR, infrared sensors, and the like weren’t enough for Big Brother to track you, researchers from Carnegie Mellon University have found a way to track human movements via WiFi. [PDF via VPNoverview]

The process uses the signals from WiFi routers for an inexpensive way to determine human poses that isn’t hampered by lack of illumination or object occlusion. The system produces UV coordinates of human bodies by analyzing signal strength and phase data to generate a 2D feature map and then feeding that through a modified DensePose-RCNN architecture which corresponds to 3D human poses. The system does have trouble with unusual poses that are not in the training set or if there are more than three subjects in the detection area.

While there are probably applications in Kinect-esque VR Halo games, this will probably go straight into the toolbox of three letter agencies and advertising-fueled tech companies. The authors claim this to use “privacy-preserving algorithms for human sensing,” but only time will tell if they’re correct.

If you’re interested in other creepy surveillance tools, checkout the Heat-Sensing Crotch Monitor or this Dystopian Peep Show.

Big Brother And Others Are Watching Your Car

We are all (hopefully) aware that we can be watched while we’re online. Our clicks are all trackable to some extent, whether it’s our country’s government or an advertiser. What isn’t as obvious, though, is that it’s just as easy to track our movements in real life. [Saulius] was able to prove this concept by using optical character recognition to track the license plate numbers of passing cars half a kilometer away.

To achieve such long distances (and still have clear and reliable data to work with) [Saulius] paired a 70-300 mm telephoto lens with a compact USB camera. All of the gear was set up on an overpass and the camera was aimed at cars coming around a corner of a highway. As soon as the cars enter the frame, the USB camera feeds the information to a laptop running openALPR which is able to process and record license plate data.

The build is pretty impressive, but [Saulius] notes that it isn’t the ideal setup for processing a large amount of information at once because of the demands made on the laptop. With this equipment, monitoring a parking lot would be a more feasible situation. Still, with even this level of capability available to anyone with the cash, imagine what someone could do with the resources of a national government. They might even have long distance laser night vision!

Facebook To Slurp Oculus Rift Users’ Every Move

The web is abuzz with the news that the Facebook-owned Oculus Rift has buried in its terms of service a clause allowing the social media giant access to the “physical movements and dimensions” of its users. This is likely to be used for the purposes of directing advertising to those users and most importantly for the advertisers, measuring the degree of interaction between user and advert. It’s a dream come true for the advertising business, instead of relying on eye-tracking or other engagement studies on limited subsets of users they can take these metrics from their entire user base and hone their offering on an even more targeted basis for peak interaction to maximize their revenue.

Hardly a surprise you might say, given that Facebook is no stranger to criticism on privacy matters. It does however represent a hitherto unseen level of intrusion into a user’s personal space, even to guess the nature of their activities from their movements, and this opens up fresh potential for nefarious uses of the data.

Fortunately for us there is a choice even if our community doesn’t circumvent the data-slurping powers of their headsets; a rash of other virtual reality products are in the offing at the moment from Samsung, HTC, and Sony among others, and of course there is Google’s budget offering. Sadly though it is likely that privacy concerns will not touch the non-tech-savvy end-user, so competition alone will not stop the relentless desire from big business to get this close to you. Instead vigilance is the key, to spot such attempts when they make their way into the small print, and to shine a light on them even when the organisations in question would prefer that they remained incognito.

Oculus Rift development kit 2 image: By Ats Kurvet – Own work, CC BY-SA 4.0, via Wikimedia Commons.

“Hello Barbie” Under The Knife

In February, Google and Mattel introduced their Hello Barbie Internet-connected toy. This Barbie has an internal microphone, a WiFi connection to Google’s voice recognition services, and a speaker to carry on a “conversation” with the targeted child.

Like the folks at Somerset Recon, we’d say that this is an Internet of Things (IoT) device that’s just begging for a teardown, and we’re totally looking forward to their next installment when they pore through the firmware.

BarbieTeardown2On the hardware front, Barbie looks exactly like what you’d expect on the inside. A Marvell 88MW300 WiFi SoC talks to a 24-bit (!) audio codec chip, and runs code from a 16Mbit flash ROM. There’s some battery management, and what totally looks like a JTAG port. There’s not much else, because all the brains are “in the cloud” as you kids say these days.

From day to day we alternate between the promise of IoT and being anti-IoT curmudgeons, so it should come as no surprise that we’re of two minds about Hello Barbie. First, there’s the creepy-factor of having your child’s every word overheard by a faceless corporation with “evil” in their mission statement (see what we did there?). Next, we’re not sure that it’s OK to record everything your child says to a toy and listen to it later, even if you are the parent. Hackaday’s [Sarah Petkus] summarized this neatly in this article.

But mostly, we’re curious about how well the thing actually works and what it will do with naughty words. And who will take on the task of reviving the Barbie Liberation Organization? Now we totally want to go out and buy one of these things.