This is the new book I published in 2017 by Apress, Springer to introduce the use of OpenCV in Processing with a custom library I developed.
Check out more details at the Apress website.
This is the new book I published in 2017 by Apress, Springer to introduce the use of OpenCV in Processing with a custom library I developed.
Check out more details at the Apress website.
05/07/2014 – The library is renamed again to Kinect4WinSDK in order not to use the prefix P or P5. It has been built in Windows 7, Kinect for Windows SDK 1.8, Java JRE 1.7u60 and Processing 2.2.1.
05/04/2014 – The library is renamed to P5Kinect according to suggestion from the Processing community, in order not to mix up with official Processing class.
28/03/2014 – The library is updated for the use of Kinect for Windows SDK 1.8, Java JRE 1.7u51 and Processing 2.1.1.
The Kinect for Processing library is a Java wrapper of the Kinect for Windows SDK. And it of course, runs in Windows platform. At this moment, I have only tested in Windows 7. The following 4 functions are implemented. All images at this moment are 640 x 480.
GetImage() returns a 640 x 480 ARGB PImage.
GetDepth() returns a 640 x 480 ARGB PImage. The image is, however, grey scale only. It resolution is also reduced from the original 13 bits to 8 bits for compatibility with the 256 grey scale image.
GetMask() returns a 640 x 480 ARGB PImage. The image is transparent in the background using the alpha channel. Only those areas with players are opaque with the aligned RGB images of the players.
Skeleton tracking is a bit complicated. The library will expect 3 event handlers in your Processing sketch. Each event handler uses one or two arguments of type SkeletonData (to be explained later). Each SkeletonData represents a human figure that appears, disappears or moves in front of the Kinect camera.
appearEvent – it is triggered whenever a new figure appears in front of the Kinect camera. The SkeletonData keeps the id and position information of the new figure.
disappearEvent – it is triggered whenever a tracked figure disappears from the screen. The SkeletonData keeps the id and position information of the left figure.
moveEvent – it is triggered whenever a tracked figure stays within the screen and may move around. The first SkeletonData keeps the old position information and the second SkeletonData maintains the new position information of the moving figure.
Please note that a new figure may not represent a real new human player. An existing player goes off screen and comes back may be considered as new.
The SkeletonData class is a subset of the NUI_SKELETON_DATA structure. It implements the following public fields:
public int trackingState; public int dwTrackingID; public PVector position; public PVector[] skeletonPositions; public int[] skeletonPositionTrackingState;
import kinect4WinSDK.Kinect; import kinect4WinSDK.SkeletonData; Kinect kinect; ArrayListbodies; void setup() { size(640, 480); background(0); kinect = new Kinect(this); smooth(); bodies = new ArrayList (); } void draw() { background(0); image(kinect.GetImage(), 320, 0, 320, 240); image(kinect.GetDepth(), 320, 240, 320, 240); image(kinect.GetMask(), 0, 240, 320, 240); for (int i=0; i =0; i--) { if (_s.dwTrackingID == bodies.get(i).dwTrackingID) { bodies.remove(i); } } } } void moveEvent(SkeletonData _b, SkeletonData _a) { if (_a.trackingState == Kinect.NUI_SKELETON_NOT_TRACKED) { return; } synchronized(bodies) { for (int i=bodies.size ()-1; i>=0; i--) { if (_b.dwTrackingID == bodies.get(i).dwTrackingID) { bodies.get(i).copy(_a); break; } } } }
It is a simple smile detection library for the open source programming environment – Processing.
Download the sample application with the library in code folder.
This is my second Processing library to implement a simple interface to the ARToolKit using the JARToolKit (obsolete).
Download the SimpleARToolKit library here.
This is the first library I write for Processing. It is, however, obsolete as the OpenCV library has already included the face detection feature.
With the introduction of the new OpenCV 4.4.0, I updated the Processing library CVImage to the latest version of OpenCV. In this version, I take out the support for Linux and the contributed library optflow.
The 2nd midi in Processing example will use the Receiver interface to capture all the midi messages during the playback of a midi file. The program uses the custom GetMidi class to implement the Receiver interface. During the playback, it will display the NOTE_ON message with information of channel, octave and note.
The source code of the example is also in the Magicandlove GitHub repository.
This is my first use of midi in Processing. I do not use the MidiBus library for Processing. Instead, I try to use the standard midi package in Java. The SE8 standard Java package also contains the javadoc documentation.
The Processing source code and sample midi files are in the Magicandlove GitHub repository. The midi example files are downloaded from the midiworld website.
The code basically needs a Synthesizer class to render midi instruments into audio and a Sequencer class to playback the midi sequence.
Synthesizer synth = MidiSystem.getSynthesizer();
Sequencer player = MidiSystem.getSequencer();
synth.open();
player.open();
All the midi music files are in the data folder of the Processing sketch. To playback each piece of midi music, we need to convert each into a Java File object and use the following code to playback it. The variable f is a File object instance containing the midi file in the data folder.
Sequence music = MidiSystem.getSequence(f);
player.setSequence(music);
player.start();
OpenCV 4.0.0 is now available in the official OpenCV.org website. I have compiled and packaged the CVImage library from my book together with the Java build of the new OpenCV library.
You can download the CVImage library here.