Robust Children Behavior Tracking for Childcare Assisting Robot by Using Multiple Kinect Sensors
Recently, the requirement for the high qualified childcare schools keeps increasing, but the number of qualified nursery teachers is far from enough. Developing a childcare assisting robot is highly necessary to help the works of nursery teachers. To work like a human nursery teacher, the first challenge for the robot is to understand the behaviors of the children automatically so that the robot can give adaptive reactions to the children. In this paper, we developed a robust children behavior tracking system by using multiple Kinect sensors. Each of the child is detected and recognized by integrating his/her personal features of face, color and motion. The tracking process is realized by using the Markov Chain Monte Carlo (MCMC) particle filter. The experiments are conducted in a childcare school to show the usefulness of our system.
KeywordsChildcare assisting robot Children behavior tracking Children recognition MCMC particle filter
This work was supported by Grant-in-Aid for Scientific Research on Innovative Areas 26118003. Special thanks to all the members in the nursery school.
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