Oh! Shiny #1: Digital photo artifacts, BIG DATA, forgery, IoT, and lie detection

An occasional curated collection of random stuff that I think is interesting

propellors

Left:Soren Ragsdale. Right: John Mitchell.

Welcome to the first of an occasional series called “Oh, shiny!” wherein I curate (‘cause that’s the groovy thing all the kewl kids are doing these days) stuff that’s attracted my attention recently but is either too short for a full post or to long to explain properly (in some cases, assuming that I actually could). So, off we go …

Rolling Shutter Artifacts Explained

Ever seen pictures such as the main photo above? Those images illustrate an imaging artifact that is caused by the way digital cameras process images and over on the excellent PetaPixel blog the post This is How Cameras Glitch with Photos of Propellers explains the problem in detail and points to an awesome web page wherein the mathematics are elucidated.

Graphing Functions

The aforementioned web page is hosted on desmos which graphs functions, plots tables of data, evaluates equations, explores transformations, and “much more – for free!”

BIG DATA

Have you ever wondered which language to use for all that BIG DATA wrangling? Python vs. R vs. COBOL: Which is best for Data Science? might just help.

No More Forgeries

R&D Magazine reports that scientists have discovered a way to authenticate or identify any object by generating an unbreakable ID based on atoms. An end to currency forgery? Possibly in the far distant future. For now, that it’ll be luxury goods such as Rolexes (Rolexi?) that will acquire anti-forgery protection first.

The Internet of Things

I’m sure you’ve been wondering how early adopters are really using the Internet of Things and, thanks to Accenture’s research reported in the Harvard Business Review, we now have an idea.

The article How People Are Actually Using the Internet of Things describes the results of an “an open-source analysis of IoT user behavior, looking at 1,000 IoT technology platforms and services and more than 279,000 early adopter interactions with IoT devices.” Spoiler alert: They found:

““The data show that the most heavily used IoT programs are ones that make home life easier, more distinctive, and more pleasant. Respondents also show a big preference for services that don’t require them to go out of their way to make something work. People using the Internet of Things increasingly prefer interfaces that are more natural and less visible (and attention-sapping) than screens. In other words, they don’t want to type instructions on a tablet, interact with a device, or mess with settings on a cell phone to get what they want. Instead, they value these technologies as “living services” that anticipate their wants and act on them.”

Lie to My Computer

Finally, MIT Technology Review reports on computer-based analysis of microexpressions, facial contortions “that appear and disappear in the blink of an eye” when people are lying or otherwise trying to hide something.

Using a database of videos  of people trying to hide their emotions, “Xiaobai Li at the University of Oulu in Finland and few pals” (sounds like a kegger was behind this work) trained a machine-learning algorithm to spot and identify microexpressions.

The results were impressive as the machine “matched human ability to spot and recognize microexpressions and significantly outperformed humans at the recognition task alone.” How long until your significant other downloads the smartphone micro expression detector and declares that it’s clear you weren’t really working late yesterday and how come there's Buffalo sauce on your tie?

Thoughts? Suggestions? Shiny stuff you want to share? Send me feedback via email or comment below then follow me on Twitter and Facebook.

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