"Analysis of the Kinect For Windows SDK 1.8 Background Removal API"
- Posted: Oct 03, 2013 at 6:00 AM
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The second post in our mini-Background Removal theme week comes from someone I don't believe I've highlighted before, but I think that's going to change...
Charles Palen takes a closer look at the official Background Removal, and having done the same thing himself, discusses how he thinks it does its magic...
This summer for the Kinect Green Screen Photo kiosk I had at Maker Faire Detroit, I invested about a month of time figuring out how to get a good mask out of the Kinect in real time. The approach I used was to ignore skeleton data, and only use depth data, then run that raw data through EMGUCV(.Net OpenCV) and do blob detection, take the detected blobs, and run them through a point by point averaging algorithm based on work done in openFrameworks. I also used a simple shader based blur effect available in Windows Presentation Foundation as it proved way faster than any other implementations I tested as well as writing my own box blur or gaussian blur. While the results I came up with are not as good as the official SDK implementation they are pretty close and don't require detected skeletons. (The project is open source, so you can check out my implementation here: https://github.com/transcendingdigital/MFDetroit2013_Kinect_GreenScreen_PhotoKiosk) Not requiring skeleton detection is a HUGE factor when groups of users are posing for photos.
How I think Microsoft's Background Removal API Works
The unfortunate part of the Microsoft Background Removal API is that it is closed source; so people like me who have been working on the same problem are interested to know exactly what is going on at a low level. I wish they would release a paper on the technique being used. Based on my own work there are a few things I am going to guess Microsoft is doing.