This post is part of Project Dance Controller.
It's a bachelor thesis project with the aim of letting the quantity of dance movements in the room control the volume level using the Kinect for Windows hardware.
You can read all reports here.
Last weekThe last week I have been going through some previous research on the area of crowd analysis and human detection. I think that the best approach for me is to use the depth image that I get from the IR sensor. This makes it easier to detect humans against cluttered backgrounds or when occlusion occurs.
The skeleton tracking only allows for tracking of two persons at the time and puts some serious restraints on poses and positions making it unusable for my scenario.
I read a research report Ikemura and Fujiyoshi where they used a depth image from an flight-of-time (FOT) camera to detect humans in real time. They used a window based approach and were able to get the detection calculations down to 100 ms on an Intel 3 Ghz CPU. Their approach was not very robust against certain poses and positions, though. It also wasn't able to handle occlusions very well.
The work of Xia, Chen and Aggarwal from the University of Texas presented a different approach to detecting humans from depth images. They used the Kinect for Xbox360 device for retrieving the depth array and detected humans in three steps. First they narrowed down all areas where a human head may be using 2D chamfer distance matching. They then confirmed all heads by fitting a 3D model onto the area. Lastly, they expanded the section from the head to include the rest of the visible body of the human. This method improves on the window based method by Ikemura and Fujiyoshi but it still suffers from some limiations. It won't work very well if the person is wearing a hat or if part of the head is hidden.
In addition to reading up on some previous research I was also able to install my newly arrived Kinect for Windows device and write a skeleton report which I will be uploading to the repository on Wednesday when I get back home again.