3-Sweep: Turning 2D images into 3D models

2d to 3d

As 3D printing continues to grow, people are developing more and more ways to get 3D models. From the hardware based scanners like the Microsoft Kinect to software based like 123D Catch there are a lot of ways to create a 3D model from a series of images. But what if you could make a 3D model out of a single image? Sound crazy? Maybe not. A team of researchers have created 3-Sweep, an interactive technique for turning objects in 2D images into 3D models that can be manipulated.

To be clear, the recognition of 3D components within a single image is a bit out of reach for computer algorithms alone. But by combining the cognitive abilities of a person with the computational accuracy of a computer they have been able to create a very simple tool for extracting 3D models. This is done by outlining the shape similar to how one might model in a CAD package — once the outline is complete, the algorithm takes over and creates a model.

The software was debuted at Siggraph Asia 2013 and has caused quite a stir on the internet. Watch the fascinating video that demonstrates the software process after the break!

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24-hour hackathon project adds object-based automation to hackerspace

hackerspace-automation

[Jeremy Blum], [Jason Wright], and [Sam Sinensky] combined forces for twenty-four hours to automate how the entertainment and lighting works at their hackerspace. They commandeered the whiteboard and used an already present webcam as part of their project. You can see the black tokens which can be moved around the blue tape outline to actuate the controls.

MATLAB is fed an image from the webcam which monitors the space. Frames are received once every second and parsed for changes in the tokens. There are small black squares which either skip to the next track of music or affect pause/play. Simply move them off of their designated spot and the image processing does the rest. This goes for the volume slider as well. We think the huge token for the lights is to ensure that the camera can sense a change in a darkened room.

If image processing isn’t your thing you can still control your audio entertainment with a frickin’ laser.

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Massively parallel CPU processes 256 shades of gray

256

The 1980s were a heyday for strange computer architectures; instead of the von Neumann architecture you’d find in one of today’s desktop computers or the Harvard architecture of a microcontroller, a lot of companies experimented with strange parallel designs. While not used much today, at the time these were some of the most powerful computers of their day and were used as the main research tools of the AI renaissance of the 1980s.

Over at the Norwegian University of Science and Technology a huge group of students (13 members!) designed a modern take on the massively parallel computer. It’s called 256 Shades of Gray, and it processes 320×240 pixel 8-bit grayscale graphics like no microcontroller could.

The idea for the project was to create an array-based parallel image processor with an architecture similar to the Goodyear MPP formerly used by NASA or the Connection Machine found in the control room of Jurassic Park. Unlike these earlier computers, the team implemented their array processor in an FPGA, giving rise to their Lena processor this processor is in turn controlled by a 32-bit AVR microcontroller with a custom-build VGA output.

The entire machine can process 10 frames per second of 320×240 resolution grayscale video. There’s a presentation video available (in Norwegian), but the highlight might be their demo of The Game of Life rendered in real-time on their computer. An awesome build, and a very cool experience for all the members of the class.

Quantifying Cloudiness with OpenCV

What Can I see From the Shard?

The Shard is the tallest building in Western Europe, and has a great view of London.  The condos in the building are very expensive, and a tourist ride to the top of the building costs £24.95.

Since the value of the view is so high, [Willem] wanted to quantify the quality of the view at any given time. His solution is the Shard Rain Cam. This device combines a Logitech webcam with a Raspberry Pi to capture a time-lapse set of images. These images are fed to a Python script using OpenCV which quantifies the cloudiness.

[Willem] also had to build a weatherproof enclosure with a transparent window for the camera and RPi. ‘Clingfilm’, which is British for saran wrap, and mineral oil is used to improve the waterproofing of an IP54 rated enclosure.

The resulting data is displayed on www.whatcaniseefromtheshard.com, which provides an indication of whether or not the view is worth £24.95. All of the Python code is available, and is a good starting point for learning about image processing with OpenCV.

DIY book scanner processes 600 pages/hour

Like any learned individual, [Justin] has a whole mess of books. Not being tied to the dead-tree format of bound paper, and with e-readers popping up everywhere, he decided to build a low-cost book scanner so an entire library can be carried in a his pocket. If that’s not enough, there’s also a complementary book image processor to assemble the individual pictures into a paginated tome.

The build is pretty simple – just a little bit of black craft board for the camera mount and adjustable book cradle. [Justin] ended up using the CHDK software for the Cannon PowerShot camera to hack in a remote trigger. The scanner can manage to photograph 600 pages an hour, although that would massively increase if he ever moves up to a 2-camera setup.

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LEGO Mindstorms Sudoku Solver

Swedish hacker [Hans Andersson] is no stranger to puzzle-solving robots. His prior work, A Rubik’s cube-solving robot called Tilted Twister, made waves through the internet last year. [Hans’] latest project only has to work in two dimensions, but is no less clever. This new robot, built around the LEGO Mindstorms NXT system, “reads” a printed sudoku page, solves the puzzle, then fills out the solution right on the same page, confidently and in ink. It’s a well-rounded project that brings together an unexpected image scanner, image processing algorithms, and precise motor control, all using standard NXT elements.

The building instructions have not yet been posted, but if the video above and the directions for his prior ’bot are any indication, then we’re in for a treat; he simply has a knack for explaining things concisely and with visual clarity. The source code and the detailed PDF diagrams for Tilted Twister are as gorgeous as his new robot’s penmanship.

[thanks Eric]

Automated Paintball Sentry

Reader, [Ben Godding], sends in the video for his senior design team’s automated paintball sentry. The frame is made of plasma cut aluminum. The paintball gun uses a custom hopper mounted remotely from the gun body. It has two webcams offering a 160 degree field of vision, and the image processing is done by a dual core pentium CPU booting windows xp off a compact flash card. The computer interfaces with the 1/4scale RC servos using a PIC24. The paintball sentry can either be configured via a computer GUI when a monitor is available or a baclkit keypad and 4×20 charachter display in the field.

Related: [Jared Bouck]‘s paintball gun turret