This post documents the final project carried out by Sama Kanbour and Afnan Fahim.

Couplets
For our final project, we built a way for people to interact with artworks using their face as a puppeteering tool. Visitors to the project use their face to distort and puppeteer images of male/female “couples”. Each half of the user’s face controls one member of the couple.

We found the couples by exhaustively searching the online image archives made available by the Metropolitan Museum of Art. We then edited these images using Photoshop to make the edges of the couples clear, and then used computer vision techniques to find contours of the bodies and/or faces of each of the couples. We then triangulated the couples, and built puppets from the resulting mesh. We then used a face-tracker to detect the facial expressions of the user, and then used this data to control the couples’ puppets.

The project was built with the openFrameworks arts-engineering toolkit, and various addons including ofxCV, ofxDelaunay, ofxPuppet, and ofxFaceTracker. Source code for the project is available here: https://github.com/afahim/Mimes

Tweet:
We brought couples from the Met museum back to life.

Abstract:
This interactive art piece brings fourteen couples from the Metropolitan Museum back to life. It allows people to discover the stories of different couples in history. Viewers can animate facial expressions of these couples by use of puppeteering. The left half of the viewer’s face puppeteers the male partner, while the right half of the face puppeteers the female partner. By using the two halves of their face, the viewer can simulate the conversation that was potentially happening between these couples back in history.

Narrative:
This interactive art piece brings fourteen carefully selected couples from the Metropolitan Museum of Art back to life. It allows people to discover the stories of different couples in history. Viewers can animate facial expressions of these couples by use of puppeteering. The left half of the viewer’s face puppeteers the male partner, while the right half of the face puppeteers the female partner. By using the two halves of their face, the viewer can simulate the conversation that was potentially happening between these couples back in history.

We desire to make historical art more tangible and accessible to today’s audience. We hope to help garner meaningful interactions between the audience and our selected artwork, and perhaps interest the audience to learn more about the artwork presented.

The piece was built using OpenFrameworks. We used Kyle McDonald’s ofxFaceTracker to detect the viewer’s facial features; ofxCV and ofxDelaunay for creating a mesh out of couples; and ofxPuppet to animate their expressions. Oriol Messia’s prototypes helped kickstart the project. The artworks were handpicked from the Metropolitan Museum of Art’s online Collections Pages. The project was carried out under supervision of Professor Golan Levin, with additional direction by Professor Ali Momeni.

Video: 
Couplets :  https://vimeo.com/96155271

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Motion Sound :  Transferring kinematics models to sound.

Overview

Motion Sound is an installation that can make sound  based on its motion.  Kinematic models (gravity, inertia, momentum) help us create a continuation of our gestures, it is a duplication of people’s gesture goes on into the future. My idea is make it to be heard.  In this project, I made a wooden bell shape pendulum. When people touch it, different sound can be triggered based on its motion.

A Longer Narrative:

When I study kinematics, I learn a lot of patterns. I always feel that there is a tight relationship between physics and sound. This idea is also inspired by Mitchel Resnick’s  BitBall  of “digital manipulatives”.

On other hands, kinematic models (gravity, inertia, momentum) help us create a continuation of our gestures, it is a duplication of people’s gesture goes on into the future. What if I can make it be heard?

My first prototype is use touchOSC app in iphone connect to max/msp to get the data of iphone’s accelerometer data and map them to sound. I 3D print a tumbler holder for iphone. Here is the video:

In the final version, I chose pendulum as kinematics model. In the hardware part, I used ardunio Nano as controller and wind sensor and accelerometer to collect data. Programming part, I used Mozzi, a sound library for arduino to design the sound effect. After some experiments, my final prototype’s sound effect sounds like a e-wind chime

I lathed a wooden bell shape shell for arduino, sensors and the speaker.

Tagline
Industrial Robot + a LED + Some Code = Painting in the physical world in all 3 dimensions

About the Project
Light painting is a photographic technique where light is moved in front of a camera taking a long exposure. The result is a streaking effect that resembles a stroke on a canvas. This is usually accomplished using a free moving handheld light source which creates paintings with lots of arcs and random patterns. While some artists can achieve recognizable shapes and figures in their paintings, they usually lack proper proportions and appear more abstracted due to the lack of real-time visual feedback while painting. Unlike traditional painting, the lines the artist makes does not persist in the physical space and is only visible using a camera. Recently, arrays of computer controlled LEDs placed on a rigid rod have allowed for highly precise paintings, but only on a single plane.

Industrial Light Painting is a project that for the first time aims to merge the three-dimensional flexibility of a free moving light with the precision of computer controlled light source. Together, these two methods allows for the creation of highly accurate, in both terms of structure and color, light paintings in full three-dimensional space. As in a manufacturing environment, an industrial robot replaces the fluid, less precise movements of a human with highly accurate and controlled motions of a machine. The automated motions of the industrial robot solves the problem of lack of visual feedback to the artist while painting in light, by allowing him or her to create the painting virtually within the software used to instruct the robot as well as the light attached to it.

How it Works
Industrial Light Painting creates full color three-dimensional point clouds in real space using an ABB manufactured IRB 6640 industrial robot. The point clouds are captured and stored using a Processing script and a Microsoft Kinect camera. The stored depth and RGB color values for each point are then fed into Grasshopper and HAL, which are plugins to Rhino, a 3-D modeler. Within Rhino, toolpath commands are created for the industrial robot which instruct the arm how to move to each location in the point cloud. Custom written instructions are also added to make use of the robots built-in low-power digital and analog lines which run to the end of the arm. This allows for precise control of a BlinkM smart LED which is mounted at the end of the arm along with a Teensy microcontroller.

Using DSLR cameras set to capture long exposures, the commanded robot movements along with precise control over the LED recreate the colored point clouds of approximately 5,000 points, within about a 25 minute period.

Result Photos

GIFS!

Process Photos

About the Creators
Jeff Crossman is a master’s student at Carnegie Mellon University studying human-computer interaction. He is a software engineer turned designer who is interested in moving computing out of the confines of a screen and into the physical world.
www.jeffcrossman.com

Kevyn McPhail is a undergraduate student at Carnegie Mellon University studying architecture. He concentrates heavily on fabrication, crafting objects in a variety of mediums pushing the limits of the latest CNC machines, laser cutters, 3D printers, and industrial robots.
www.kevynmc.com

Special Thanks To
Golan Levin for concept development support, equipment, and software.
Carnegie Mellon Digital Fabrication Lab for proving access to its industrial robots.
Carnegie Mellon Art Fabrication Studio for microcontroller and other electronic components.
ThingM for providing BlinkM ultra bright LEDs

Additionally the creators would like to thank the following people for their help and support during the making of this project: Mike Jeffers, Tony Zhang, Clara Lee, Feyisope Quadri, Chris Ball, Samuel Sanders, Lauren Krupsaw

Computationally generating raps out of TED talks.

About

TEDraps is a project by Andrew Sweet and Emily Danchik.
We have developed a system which allows for the creation of computationally-generated, human-assisted raps from TED talks. Sentences from a 100GB corpus of talks are analyzed for syllables and rhyme, and are paired with similar sentences. The database can also be queried for sentences with certain keywords, generating a rap with a consistent theme. After the sentences for the rap are chosen, we manually clip the video segments, then have the system squash or stretch them into the beat of the backing track.

Text generation

We scraped the TED website to generate a database of over 100GB of TED talk videos and transcripts. We chose to focus on TED talks because most of them have an annotated transcripts with approximate start and end points for each phrase spoken.

Once the phrases were in the database, we could query for phrases that included keywords. For example, here is the result of a query for swear words:

Here is another example of a query, instead looking for all phrases that start with “I”:

Using NLTK, we were able to analyze the corpus based on the number of syllables per phrase and the rhymability of phrases. For example, here is a result of several phrases that rhyme with “bet”:

to the budget
to addressing this segment
of the market
in order to pay back the debt
that the two parties never met
I was asked that I speak a little bit
Then the question is what do you get
And so this is one way to bet
in order to pay back the debt

Later, we modified the algorithm to match up phrases which rhymed and had a similar number of syllables, effectively generating verses for the rap. We then removed the sentences that we felt didn’t make the cut, and proceeded to the audio generation step.

Audio generation

Once we identified the phrases that would create the rap, we manually isolated the part of each video that represented each phrase. This had to be done by hand, because the TED timestamps were not absolutely accurate, and because computational linguistic research has yet to develop a completely accurate computational method for separating spoken word.

Once we had each phrase on its own, we applied an algorithm to squash or stretch the segment to the beats per minute of the backing track. For example, here is a segment from Canadian astronaut Chris Hadfield’s TED talk:
First, the original clip:

Second, the clip again, stretched slightly to fit the backing track we wanted:

Finally, we placed the phrase on top of the backing track:

We did not need to perform additional editing for the speech track, because people tend to speak in a rhythmic pattern on their own. By adding ~15 rhyming couplets together over the backing track, we ended up with a believable rap.

Tweet:

Witness THE ENCOUNTER of two complex creatures. Teaching and learning causes a relationship to bloom.

Abstract:

“The Encounter” tells the tale of two complex creatures. A human and industrial robotic arm meet for the first time and engage in an unexpected playful interaction, teaching and learning from each other. This story represents how we, as a society, have grown to learn from and challenge technology as we move forward in time. Using Touch Designer, RAPID, and the Microsoft Kinect we have derived a simplistic theatrical narrative through means of experimentation and collaboration.

Narrative:

During the planning stages of the capstone project, Golan Levin introduced us, the authors of the piece, to one another saying that we could benefit from working with each other. Mauricio, from Tangible Interaction Design, was wanting to explore the use of the robotic arm combined with mobile projections, while Kevan, from the School of Drama VMD, was wanting to explore interactive theatre. This pairing ended up with the two of us exploring and devising a performative piece from the ground up. In the beginning, we had no idea what story we wanted to tell or what we wanted it to look like. We just knew a few things we wanted to explore. We ultimately decided to let our tests and experiments drive the piece and let the story form naturally from the playing between us, the robot, the tools, and the actress, Olivia Brown.

We tried out many different things and built different testing tools. Such as a way to send Kinect Data from a custom TouchDesigner script through a TCP/IP connection so that RAPID could read it and allow the robot to move in sync with an actor. This experiment proved to be a valuable tool and research experience. Also a Processing sketch was used during the testing phases to evaluate some of the robot’s movement capabilities and responsiveness. Although we ended up dropping this from the final performance for more cue based triggering, ultimately the idea of the robot moving and responding to the humans movement drove the narrative of the final piece.

We had planned many different things, such as using the entire dFab (dfabserver.arc.cmu.edu) lab space as the setting for the piece. This would have included multiple projector outputs/ rigging, further planning, extra safety precautions for our actress, etc. Little did we realize that this would have been trouble for us due to the quickly shortening deadline. Four days before we were suppose to have our performance, an unexpecting individual came with a few words of wisdom for us. “Can a robot make shadow puppets?”. Yes, Golan’s own son’s curiosity was the jumping off point for our project to come together not only visually, but also realistically for time sake. From that moment on we set out to create a theatrical interactive robotic shadow performance. The four days included researching the best way to set up the makeshift stage in the small confines of dFAB and finishing the performance as strong as we could. To make the stage, we rigged unistrut (lined with velcro) along the pipes of the ceiling. From there we used a Velcro lined RP screen from the VMD department and attached it to the unistrut and two Autopoles for support. This created a sturdy/clean looking projection/shadow surface to have in the space.

Conceptually we used two different light sources for the narrative. A ellipsoidal stage light and a 6000 Lumen Panasonic Standard Lens Projector. In the beginning of the piece, the stage light was used to cast the shadows. Through experimenting with light sources, we found that this type of light gave the “classic” shadow puppet atmosphere. It gave it a vintage vibe of the yesteryears before technology. As the story progresses and the robot turns on, the stage light flickers off while the digital projector takes over as the main source of light. This transition is meant to show the evolution of technology being introduced to our society while expressing the contrast between analog and digital.

The concept for the digital world was that it would be reactive to both the robot and the human inputs. For example the human brings an organic life to the world. This is represented through the fluctuation of the color spectrum brought upon the cold muted world of the robot. As this is the robot’s world, as it moves around the space and begins to make more intricate maneuvers, the space responds like a machine. Boxes push in and out of the wall, as if the environment is alive and part of the machine. The colors of the world are completely controlled by the actress during the performance, while the boxes where cue based. They used noise patterns to control the speed of movements. If there was one thing would be great to expand on, it would have been for the robot’s data to be sent back to TouchDesigner so that it would live control the box’s movements instead of it being cued by an operator.

For the robots movements, we ended up making them cue based for the performance. This was done directly in RAPID code, cued from an ABB controller “teach pendant”; a touch and joystick based interface for controlling ABB industrial arms. We gave the robot pre planned coordinates and movement operations to do based on rehearsals with the Actress. One thing we would love to expand on further is to allow the recording of the Actress’ movements so that we can play them back live instead of pre defining them in a staged setting. In general we would love to make the whole play between the robot and human more improv rather than staged. Yet, robotic motion proved to be the main challenge to overcome, since the multitude of axis (hence possible motions) of the machine we used (6 axis), makes it very easy to inadvertently reach positions where the robot is “tangled”, and will throw an error and stop. It was interesting to know, specially working on this narrative, that this robotic arms and their programming workflows do not provide any notion of “natural motion” (as in the embodied intelligence humans have when moving their limbs in graceful and efficient manners, without becoming blocked with oneself, for example), and are definitely not targeted towards real time input. This robots are not meant to interact with humans, which was our challenge both technically and to our narrative.

In the end we created a narrative theatrical performance that we feel proud of. One that was created through much discussion and experimenting/play in the dFAB lab. There is much potential for more in this concept, and we hope to maybe explore it further one day!

Github:

https://github.com/maurothesandman/IACD-Robot-performance

https://github.com/kdloney/TouchDesigner_RoboticPerformance_IACD

***The TouchDesigner github link is currently the old file used during rehearsals. The final file will be uploaded at a later date due to travel and insufficient file transfers.

 SPECIAL THANK YOU:

Golan Levin, Larry Shea, Buzz Miller, CMU dFAB, CMU VMD, Mike Jeffers, Almeda Beynon, Anthony Stultz, Olivia Brown, and everyone that was involved with Spring 2014 IACD!

Best,

Kevan Loney

Mauricio Contreras

Young readers bring storybook characters to life through the Looking Glass.

Looking Glass explores augmented storytelling. The reader guides the Looking Glass over the pages in a picture book and animations appear on the display at set points on the page. These whimsical animations bring characters to life and enable writers to add interactive content.

I was inspired to create this project after seeing the OLED display for the first time. I saw the display as a looking glass through which I could create and uncover hidden stories. Storybooks were an ideal starting point because of a younger readership that is these days very eager to use technology like tablets and smartphones. However unlike a tablet, Looking Glass requires the book and more importantly requires the reader to engage in the book.

For more technical details please see this prior post.