The new Kinect for Windows SDK library is now officially listed under the Libraries section of the Processing website. Please try and test. Feedback welcome.
The new Kinect for Windows SDK library is now officially listed under the Libraries section of the Processing website. Please try and test. Feedback welcome.
The Kinect for Windows SDK library for Processing is renamed again to cater for the naming convention in the Processing standard. It is now called Kinect4WinSDK. The main class is Kinect, instead of P5Kinect or PKinect.
The new library is built in Windows 7, with Java JRE 1.7u60, Kinect for Windows SDK 1.8, and tested in Processing 2.2.1.
To work with the official Processing library naming convention, the Kinect for Windows SDK library was renamed to P5Kinect. You can download the new library from the original page at http://www.magicandlove.com/blog/research/kinect-for-processing-library/.
Happy coding.
The updated library is now ready. Please download at my research page. The source is also updated at the corresponding Github page.
Finally, I updated the original PKinect Processing library for the Microsoft Kinect camera with the latest Kinect for Windows SDK 1.8 and built with Java JRE 1.7 update 51. It was tested in the latest Processing version 2.1.1.
The testing library can be temporarily downloaded here. Place the code folder into your Processing sketch folder. The latest sources will be released in Github soon.
The following Processing codes demonstrate the use of the OpenCV Features2D to detect key points from the webcam image. It is the first part of a more complex task to identify 3D motion from a 2D image.
This is the original OpenCV people detection example ported to Processing with the Java library of OpenCV 2.4.8. It can achieve more than 20 frames per second. Here is a sample test snapshot.
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I use the motion template Processing program in the previous post to render a number of classic film sequences from IGN. Through the motion components returned from each frame, I draw a square by picking up the colour of the pixel at that location.
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The following example ported the original OpenCV motion template sample code in C to Java/Processing. The original source is the motempl.c file in the OpenCV distribution.
The program started using the default video capture device and passed it to the class Motion. It employed the accumulated difference images to segment into different motion regions, delivered back with a list of rectangles, indicating where the motion components are. It then returned to the Processing main program with an ArrayList of the class Result.
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