Years ago I wanted to implement PTAM. I was young and naïve 🙂
Well I got a few moments to spare on a recent sleepless night, and I set out to implement the basic bootstrapping step of initializing a map with a planar object – no known markers needed, and then tracking it for augmented reality purposes.
Tag: tracking
Just sharing a simple recipe for a video stabilizer in OpenCV based on goodFeaturesToTrack() and calcOpticalFlowPyrLK().
Well… it’s a bit more than 20 lines, but it is short. And it doesn’t work for every kind of video (although the results are funny anyway! :).
I wish to report of a number of tweaks and additions to the hand silhouette tracker I posted a while back. First is the ability for it to “snap” to the object using a simple Active Snake method, another is a more advanced resampling technique (the older tracker always resampled after every frame), and of a number of optimizations to increase the speed (tracker now runs at real-time on a single core).
I wanna share some code for 2D curve tracking with a particle filter, implementing the body of work of Tony Heap and David Hogg. These guys presented a relatively easy to implement method for tracking deformable curves through space and change in form using a Hierarchical Point Distribution Models (HPDM), which is another elegant way to store shape priors. Granted, it is not perfect, but for a simple 2D shape like a hand it works pretty good, and rather fast as well.
Let’s dive in then,
Hi,
I wanted to put up a quick note on how to use Kalman Filters in OpenCV 2.2 with the C++ API, because all I could find online was using the old C API. Plus the kalman.cpp example that ships with OpenCV is kind of crappy and really doesn’t explain how to use the Kalman Filter.
I’m no expert on Kalman filters though, this is just a quick hack I got going as a test for a project. It worked, so I’m posting the results.