This video is a sample run of the artwork – Movement in Time, with only 4 clips. They are:
- Jazz Singer
- Ben Hur
- North by Northwest
- Psycho
OpenCV
Some thoughts about the recent OpenCV and films works
It is about time to write up something about the recent works (post 1, post 2) that I have done with OpenCV and the classic film sequences. I started the recent version of the project first for the submission to the Image Conference in Berlin and then the Microworld exhibition in Hong Kong. The software I have been testing is the OpenCV library, openFrameworks and Processing. For the final show, I may choose openFrameworks for performance and stability reasons.
Rendering of classic film sequences with OpenCV optical flow
Here are another testing images with the use of OpenCV optical flow algorithms to render a number of classic film sequences.
- Beauty and the Beast
- Lady and the Tramp
- Some Like it Hot
- The Princess Bride
OpenCV Features2D in Processing
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.
People Detection in Processing with OpenCV
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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Motion Template Rendering of Classic Film Sequences
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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OpenCV Motion Template Example in Processing
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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Conversion between Processing PImage and OpenCV cv::Mat
This example illustrates the use of the Java version of OpenCV. I built the OpenCV 2.4.8 in Mac OSX 10.9. After building, I copied the following two files to the code folder of the Processing sketch:
- opencv-248.jar
- libopencv_java248.dylib
The program initialised the default video capture device. It converted the PImage first into an OpenCV matrix – Mat. The matrix is duplicated into another copy and then converted back to another PImage for display with the image command.
It can achieve around 60 frame per second in my old iMac. Here is the screenshot.
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Build OpenCV on Mac OSX
When I posted the use of OpenCV in Processing, there were a number of queries about installing and building OpenCV in OSX. In this post, I try to summary the process. It assumes basic understandings of the Unix environment of the OSX system with the use of the Terminal command. Here are the steps.