This is to let you know that I have released a new update to the cv.jit computer vision library.
Version 1.6 is now distributed as a true universal binary on OSX.
Apart from that, there are relatively few changes.
Two new externals have been added:
cv.jit.shift implements the MeanShift and CAMShift trackers which allow for relatively efficient and robust tracking of regions in a greyscale image.
cv.jit.resize, well, resizes. Since bicubic interpolation is used, down-sampled matrices will appear anti-aliased.
Some minor changes to existing objects:
There is now no limit to the number of points cv.jit.track can track at the same time. Of course, you should expect sluggish performance for very large number of points but 255 is no longer a hard-coded limit.
You can now query cv.jit.faces for the number of detected faces. This makes it easier to filter the dummy matrices that are output when no face has been detected.
cv.jit.features can now also compute features with sub-pixel accuracy for better tracking initialization.
On OSX, cv.jit.erode and cv.jit.dilate now use Core Image which means they now run much, much faster.
A number of bugs have also been fixed.
This first beta has been tested on Windows XP, Mac OS 10.4 with both Intel and PPC machines. It has not yet been tested on Vista or OS 10.5, though I do not think there should be any problem.
As always, I appreciate bug reports and comments!
Hope this will come useful.
Jean-Marc