Face Detection and Tracking for Human Robot Interaction through Service Robot

In our approach, a method is proposed to accomplish face detection and human tracking. In the realtime application such as robot system, the initialization and lost track problems often limit the application. The method which combines with face detection algorithm based on AdaBoost and the object tracking method using Kalman filter is proposed in this paper. To carry out the initialization problem, the global AdaBoost face detection (GAFD) algorithm is applied. It is powerful to detect multiple faces in the whole image. If there is a new face in image, a new face tracker and the new local AdaBoost face detection (LAFD) are both generated. The tracker will predict the possible area of the face appearing. According to the prediction of the tracker, partial image which is called region of interest (ROI) is obtained for LAFD. In the experimental result, our approach has been successfully implemented and test on service robot for human tracking. It is useful for the application of human-robot interaction.

I. Introduction

The autonomous robot becomes a growing interest and a popular subject and has been implemented widely in many areas. Traditionally, the robots have used in helping the workers in the fields of industrials and science such as semiconductor factories. Nevertheless, in the near years the robots are expected to provide all kinds of service in humandaily lives. In the fundamentals, the developed service robot has the following functions to perform such the specific and securityservice:autonomousnavigation, supervisesthrough internet, a remotely operated camera vision system, human-robot interaction (HRI) and so on.