Flexible Action and Articulated Skeleton Toolkit Contributors Evan A. Suma, Belinda Lange, Skip Rizzo, David Krum, and Mark Bolas Project Email Address: faast@ict.usc.edu 32-bit(recommended for most users) 64-bit(for advanced users) Note from Evan Suma, the developer of FAAST: I have recently transitioned to a faculty position at USC, and unfortunately that means I have very limited time for further development of the toolkit. You may also view our online video gallery, which contains videos that demonstrate FAAST’s capabilities, as well as interesting applications that use the toolkit. Have a Kinect for Windows v2? We have developed an experimental version of FAAST with support for the Kinect for Windows v2, available for download here (64-bit only). Recent News December 12, 2013 FAAST 1.2 has been released, adding compatibility for Windows 8. Summary FAAST is middleware to facilitate integration of full-body control with games and VR applications using either OpenNI or the Microsoft Kinect for Windows skeleton tracking software. E. Support
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Kinect for Windows Software and Multitouch Monitors avin2/SensorKinect - GitHub The Khronos Group Inc. Kinect PowerPoint Control Trackmate 1. Print Tags Trackmate uses a small, specially designed circular barcode that stores information which can be easily decoded by the Trackmate Tracker. The tag measures less than 1"x1" square, contains a six byte unique ID (over 280 trillion unique IDs are possible), and is entirely open source. Download the Trackmate Tagger for Windows, Mac OS X, or Linux to create your own sets of randomly generated tags and print them from your computer. 2. There are a lot of different ways that you can build a Trackmate system. 3. The Trackmate Tracker reads Trackmate tags (by processing images from a webcam) and then sends the corresponding data to any spatial application via LusidOSC. 4. Trackmate sends object data via LusidOSC (a protocol layer for unique spatial input devices), allowing any LusidOSC-based application to work with the system.
Interactive Media Division Throughout the course of my degree progress, one debate raised our very first class meeting of our first year was the concept of traditional authorial narrative vs. emergent narrative. Traditional authorial narrative is what we’ve come to know as our film-based non-interactive media, whereas emergent narrative is procedurally generated by way of a designed system. As I head towards the end of my second year, it’s less of a balanced argument— traditional narrative in games (Ludus, as named by Roger Callois in Man, Play and Games,) seem to be relying on their predecessors as a clutch, while systemic narrative (Paidia) is beginning to show the uniqueness of the new medium that we’re witnessing mature before our eyes. This actually has to do with the concept of “free will”. It makes sense that earlier, more primitive games are more ludus-based, as most of them pre-date multilateral gameplay. Before the advent of the home console, we would go to the coin-operated video game arcade.
MinGW | Minimalist GNU for Windows Why Do We Need Limits and Infinitesimals? So many math courses jump into limits, infinitesimals and Very Small Numbers (TM) without any context. But why do we care? Math helps us model the world. We can break a complex idea (a wiggly curve) into simpler parts (rectangles): But, we want an accurate model. The tricky part is making a decent model. The Paradox of Zero Breaking a curve into rectangles has a problem: How do we get slices so thin we don’t notice them, but large enough to “exist”? If the slices are too small to notice (zero width), then the model appears identical to the original shape (we don’t see any rectangles!). If the slices are tiny but measurable, the illusion vanishes. We want the best of both: slices so thin we can’t see them (for an accurate model) and slices thick enough to create a simpler, easier-to-analyze model. The Solution: Zero is Relative The notion of zero is biased by our expectations. Well, “i” sure looks like zero when we’re on the real number line: the “real part” of i, Re(i), is indeed 0. Summary
Nicolas Burrus Homepage - Kinect Calibration Calibrating the depth and color camera Here is a preliminary semi-automatic way to calibrate the Kinect depth sensor and the rgb output to enable a mapping between them. You can see some results there: It is basically a standard stereo calibration technique ( the main difficulty comes from the depth image that cannot detect patterns on a flat surface. Thus, the pattern has to be created using depth difference. Here I used a rectangular peace of carton cut around a chessboard printed on an A3 sheet of paper. Calibration of the color camera intrinsics The color camera intrinsics can be calibrated using standard chessboard recognition. Calibration of the depth camera intrinsics This is done by extracting the corners of the chessboard on the depth image and storing them. Transformation of raw depth values into meters Raw depth values are integer between 0 and 2047. Stereo calibration Color Depth
Hugin - Panorama photo stitcher