Created by Teehan+Lax Labs, Touch Vision Interface is a combination of software and hardware to allow realtime manipulation of content on a remote device via touch interface on a mobile device. Instead of purely using mobile device screen as an input, the user views the remote content and applies the content simultaneously, better know but not necessarily a form of AR.

I can still recall the first time I saw an Augmented Reality demo. There was a sense of wonderment from the illusion of 3D models living within the video feed. Of course, the real magic was the fact that the application was not only viewing its surrounding environment, but also understanding it. AR has proven to be an incredible tool for enhancing perception of the real world. Despite this, I’ve always felt that the technology was somewhat limited in its application. It is typically implemented as output in the form of visual overlays or filters. But could it also be used for user input? We decided to explore that question by pairing the principles of AR (like real-time marker detection and tracking) with a natural user interface (specifically, touch on a mobile phone) to create an entirely new interactive experience.

Continue reading.... Touch Vision Interface [openFrameworks, Arduino, Android]

Created by Naoki Nishimura, Helvetica Face is a Livetype format font. This new Helvetica family font changes the “typeface” based on the posting of a new “face”. The site allows you to record your face within the font, adjusting the threshold resulting in a new glyph you can download.

While normal fonts which are governed by software rules on how to show the internal form (=data), Helvetica Face doesn’t have this internal information on the form. What is does have is external data given in the shape of a image of your face, and how to show that form is the only rule. For that reason, through the given data, the form continues to change without bounds.

Livetype is a new font format which takes a variety of data and can change the form of it in real time.

livetype.in/face/

Music video for Catalina, a track off the Chocolat EP by Moullinex, released in January on Gomma Records created using Kinect + Processing + Cinema 4D + After Effects.

We started with the Kinect interface library developed for Processing and made available by Daniel Shiffman. Some modifications were introduced, to get our 3D data into Cinema 4D. Each file represents one frame with a coordinate map (point index, x, y, z lines) in plaintext. A threshold filter was added to enable us to filter out any points that were too far. This way we could remove the living room entirely from the sequence. Importing files manually into Cinema 4D would be painful/impossible, so we wrote a little python script that read these files in real-time, allowing us to tweak playback speed, resolution, etc. After importing all our scenes into Cinema 4D, the rendered sequences were taken into After Effects and Premiere. Business as usual from here on.

Detailed walkthrough is available here including Cinema 4D files download and Processing code.

Concept: Luis Clara Gomes, Luis Calçada
Visuals: Luis Calçada
Programming: Luis Clara Gomes
Editing: Francisco Costa
also Joana Nobre and Paulo Raimundo

Buy the EP here, or listen to the tracks on soundcloud.

/via Zach

Fluid Vase is an object designed by simulating fluid action. The aim was to translate actions commonly associated with an object into the object itself, which in this case is the action of pouring water into a vase. A high speed camera was used to capture actual water motion in vases of different shapes at 500 frames per second. Simulations in Processing were then based on these footages to produce a 3D virtual mesh.

In this vision, consumers would have various options such as the speed and volume of water, and be able to select a frame from the simulation. Production is then done on demand using 3D printing.

Created by Fung Kwok Pan (fungkwokpan.com)
Soon available for purchase at supabold.com

Color a Sound is a sound installation by Blair Neal, that invites participants to color on a transparency and hear a corresponding sound. Sound is triggered when it passes a line, observed by MaxMSP software running in the background. Different colors control the octave of a note, blue – low, green – middle and red – high. Modes can also be changed so that blue colours trigger 808 drum sounds instead of chimes.

The interaction is meant to be very simple and playful, hence the major scale. It would be much more difficult for someone to walk up and have fun with a chromatic scale. Like any instrument, one would have to spend a lot of time to make a composition worth listening to and this is just a demo of the sonic abilities/responsiveness.

If you would like a copy of the “ugly max patch” send Blair a message on vimeo.

(via SaturnNeverSleeps)

For more MaxMSP projects on CAN, see here.

Buttons in a project by Sascha Pohflepp playing on the notion of the camera as a networked object. Unlike a conventional analog or digital camera, this one doesn’t have any optical parts. It is a camera that will only capture a moment at the press of a button by recording only the time it was pressed. Quickly after it begins to continuously search on the net for other photos that have been taken in the very same moment and displays on the screen. Essentially, it is a camera that – using a SonyEricsson K750i hidden behind the boxing – takes other’sphotos. Photos that were created by someone who pressed a button somewhere at the same time as its own button was pressed.

Taking a photo means making a memory. Choosing a moment in time and framing a situation. Archiving it or making it public. Either way, we create a visual item that we have an emotional attachment to through our memory. Photos help us to remember moments in our past. Often they even become a memory in their own right. For many, making their moments public through services like Flickr is already part the process of photography itself, creating archives which contain a vast collection of visual fragments of individual lives.

Built with Processing / Mobile Processing. Photo search using the Flickr API.

This project was conceived by Sascha Pohflepp as a diploma thesis in Visual Communication at the Berlin University of the Arts (UDK). It was supervised by prof. Joachim Sauter and Jussi Ängeslevä.

blinksandbuttons.net

(via random-magazine)

See also Social Collider [WebApp]

Created by Mary Huang, TYPEFACE is a study of facial recognition and type design, creating a typeface that corresponds to each individual, like a typographic portrait. Somewhat similar to LAIKA project – interactive typeface, the challenge here were the limitations of geometric type system, being able to allow for a great amount of variation while maintaining a general level of quality in the letters. This was made especially harder by using lowercase letters.

…people really wanted to do was make funny faces at the camera so they could watch the type change. So, I decided to encourage that. I also wanted to draw a closer connection to handwriting, so I added the ability to type in the program, which creates sentences with accumulated variation in the letters.

For more information visit rhymeandreasoncreative.com. For Mary’s full portfolio, visit the website here.

TYPEFACE was created using Processing.

UPDATE 27.07.2010: App is now available for DOWNLOAD.

In cooperation with Christien Meindertsma, Nils Völker developed an installation for Christien’s exhibition at the MU in Eindhoven (Netherlands). The exhibition was called “Makers & Spectators” and was about the human perception and the way we look at things.

The installation consists out of two parts. A viewing box with replaceable Images of a range of different objects like a chicken, a slice of bread and much more. While the visitor is looking at one of these images an eye-tracker within the viewing box records the movement of the eyes. The second part is the robot, hanging on three ropes from the ceiling on top of a large pile of paper sheets. It reproduces each point the visitor has looked at with a thick marker on the Paper by moving the same way as the eyes did.

There are two Lego NXT (Mindstorm) bricks on this robot, one for the movement and one controlling the pen. Both communicate via bluetooth and are powered by rechargeable batteries, permanently plugged to battery chargers from the ceiling. The process is started as soon a visitor is looking long enough at an image of an object that is inside a viewing box. An eye-tracker records the eye movement into x/y-coordinates. Then this data is saved into a txt-file and sent to the robot via a very long USB-cable. The program on the robot, written in NXC, reads the txt-file and moves to appropriate coordinates.

See + read more at Nils Völker – Robotics – Dotje.

(via @isaac_topo)

A project by Evan Roth with software development by Chris Sugrue, Graffiti Analysis 2.0 is a openFrameworks application that tracks motion of a graffiti tag and represents it digitally in three dimensions, accompanied by particle effects, somewhat stylised generative animations are generated.

Inspired by what began as his thesis project Graffiti Taxonomy and his involvement in the Graffiti Research Lab, Evan continues to explore Graffiti typography. Amongst many other things he is also in the process of co-founding F.A.T. (Free Art & Technology), Brooklyn’s first and only R&D lab for the public domain. Evan studied Parsons Design + Technology MFA program where he now teaches subjects ranging from visual programming to internet fame to geek graffiti (a course labeled “an invitation to break the law” by city council member Peter Vallone Jr.). You can read more about Evan and see his other work at evan-roth.com

Graffiti Analysis 2.0 software is still in development but the source code and downloads will be made available soon on evan-roth.com.

(via Zach)

Crash Photography is a project by Greg Borenstein, a programmer, musician, hardware hacker, and student at NYU ITP in New York City. Using MatchBox cars and Arduino board, Greg constructed a realtime camera shutter of crash event occurring from two cars colliding. As the undercarriages of cars were conductive enough to set off the multi-meter, as they touch, they set off Arduino to blink the built-in extra strong LED lights. As the camera shutter is left open, LED lights provide sufficient illumination to take a visible picture. The results, as you can see below, are beautiful images of something truly special captured. Whilst one may consider that this could be easily replicated or faked, what is impossible to achieve is the motion blur captured from cars moving.

A wonderful mix of physical and digital, connected to,gether to create something we could have never been able to see otherwise. Just wonderful…

To read more, get the Arduino code and get all the details on the project see urbanhonking.com

Crash Photography with Arduino and MatchBox Cars