Pinokio is an exploration into the expressive and behavioural potentials of robotic computing. Customized computer code and electronic circuit design imbues Lamp with the ability to be aware of its environment, especially people, and to expresses a dynamic range of behaviour. As it negotiates its world, we the human audience can see that Lamp shares many traits possessed by animals, generating a range of emotional sympathies. In the end we may ask: Is Pinokio only a lamp? – a useful machine? Perhaps we should put the book aside and meet a new friend.
New technology from Japan can monitor all shop visitors, discerning age, gender, and visiting frequency, and measures the data with a system called ‘NeoFace’, all with a normal PC and webcam - via DigInfo (video embedded below):
NEC has developed a marketing service that utilizes facial recognition technology to estimates the age and gender of customers, and accumulates the data, along with the dates and times that customers visit stores. This data is then used to analyze trends in customer behavior and visit frequency.
This service is provided in Japan via NEC’s cloud computing technology, only requires a regular PC and video camera, and is available for approximately $880 (70,000 yen) per month per store.
“This service is mainly intended for retailers that have several stores. It provides retailers with customer attributes based on facial images. That information is helpful for sales strategies.”
This service can also detect repeat customers across multiple stores. It uses a face detection and comparison engine developed by NEC, called NeoFace.
CORRECTION: blech said: The author of the original code is Phil McCarthy, twitter.com/phl / GitHub.com/phl
Online coding experiment by Adam Norwood combines a random polygon generator constantly making shapes along with a facial recognition algorithm - from Adam’s Tumblr:
What happens if you write software that generates random polygons and the software then feeds the results through facial recognition software, looping thousands of times until the generated image more and more resembles a face? Pareidoloop. Above, my results from running it for a few hours. Spooky.
(More about the project on GitHub, and more about pareidolia in case the name doesn’t ring a bell)
Works better (and faster) in Chrome, you can try it out here
(PS - if you can’t see the animated GIFs at the top, click on them and they should appear …)
Some great reading material if you are looking for some background in contemporary tech / media art. Put together by Kyle McDonald, it covers areas such as facial recognition, the Kinect, Glitch and 3D scanning. While not all of it maybe relevant to the regular reader, there are plenty of links of examples to works and some contextual information.
A seven week course, the final week includes examples of works completed by course attendees.
Design project by Neil Usher that identifies faces in clouds:
Robots are designed to perform precise and repetitive operations with relentless efficiency, performing the tasks we find too laborious or dangerous. However, could these robots be deployed to improve the efficiency of our leisure time by performing tasks we enjoy? Could intelligent machines bird watch for us or look for four-leaf clovers? Could they optimise our pastimes, searching for patterns and spectacle in nature that would be imperceptible or too time-consuming for us to find for ourselves?
Combining ‘Word With Friends’, facial recognition and Google Hangouts, your mouth becomes a mouse pointer. Put together by Aaron Meyers and OKFOCUS got the Google+ Hackathon - video below:
Welcome to Draw With Your Face, the fast-paced drawing and guessing game where your FACE is your PAINTBRUSH! Jump into a hangout with up to 9 friends, open up your mouth and say “AHHHHHHH” (the sound from your mic starts and stops your brushstrokes). You’ve got 2 minutes to get your friends to guess your word. The first player to correctly guess what you’re drawing scores (and you do to)! Share your best drawings on Google+. Are you ready to draw like you’ve never drawn before?
More info and links can be found here, and the development blog on Tumblr can be found here
Created by Adam Harvey, this on-going project examines and experiments with creative ways to protect yourself from facial-recognition technology. I have posted about this before over a year ago, but it is interesting to see where the project has been going … hair and make-up could be the future hoodie …
CV Dazzle™ is camouflage from computer vision (CV). It is a form of expressive interference that combines makeup and hair styling (or other modifications) with face-detection thwarting designs. The name is derived from a type of camouflage used during WWI, called Dazzle, which was used to break apart the gestalt-image of warships, making it hard to discern their directionality, size, and orientation. Likewise, the goal of CV Dazzle is to break apart the gestalt of a face, or object, and make it undetectable to computer vision algorithms, in particular face detection.
Because face detection is the first step in automated facial recognition, CV Dazzle can be used in any environment where automated face recognition systems are in use, such as Google’s Picasa, Flickr, or Facebook.
Hye Yeon Nam - Please Smile (Robotic Installation, 2011)
Interactive installation featuring five skeleton arms, whose hands react in unison based on facial gestures - if you smile and wave ‘hello’, all hands wave back …
“Please smile” is an exhibit involving five robotic skeleton arms that change their gestures depending on a viewer’s facial expressions. Audiences interact with “Please smile” in three different ways. When no human falls within the view of the camera, the five robotic skeleton arms choose the default position, which is bending their elbows and wrists near the wall. When a human steps within the view of the camera, the arms point at the human and follow his/her movements. Then when someone smiles in front of it, the five arms wave their hands.
“If you change the contrast in certain parts of your face — either through a watermark or by wearing a strategically-placed sticker or facepaint, recognition technology can’t identify that your face is a human face.”