Human Activity Recognition from Kinect Captured Data Using Stick Model

In this paper authors have presented a method to recognize basic human activities such as sitting, walking, laying, and standing in real time using simple features to accomplish a bigger goal of developing an elderly people health monitoring system using Kinect. We have used the skeleton joint positions obtained from the software development kit (SDK) of Microsoft as the input for the system. We have evaluated our proposed system against our own data set as well as on a subset of the MSR 3Ddaily activity data set and observed that our proposed method out performs state-of-the-art methods.