Human Identification through Kinect’s Depth, RGB, and Sound Sensor
Parameswari Shunmugam, Kamarulzaman Kamarudin, A A A Mosed, Shazmin Aniza Abdul Shukor · IOP Conference Series Materials Science and Engineering · 2019
Abstract Human identification is a very important subject in computer field and has been researched widely. This paper proposes human identification system based on Kinect’s individual sensor as well as combination of all its available sensors. In the first part of the project, each sensor on the Kinect (i.e IR depth sensor, RGB camera and microphones) was used for skeleton recognition, face recognition and speech recognition respectively. Then, these individual recognition methods are combined as step-by-step process into a multi-sensor recognition system. Few experiments were carried out to test the reliability of the developed human identification systems. The results show that multi-sensor based human identification system is highly efficient compared to the single-sensor system. This is because, multi-sensor recognition system involves many recognition stages as each recognition stage needs particular biometric information of the user.