Author(s)

Bin Zhang¹, Tomoaki Nakamura¹, Rena Ushiogi², Takayuki Nagai¹, Kasumi Abe¹, Takashi Omori³, Natsuki Oka⁴, Masahide Kaneko¹

¹Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo, Japan.
²Faculty of Home Economics, Otsuma Women’s University, Tokyo, Japan.
³Department of Intelligent Mechanical Systems, Tamagawa University, Tokyo, Japan.
⁴Faculty of Information and Human Sciences, Kyoto Institute of Technology, Kyoto, Japan.

Developing a childcare assisting system is highly necessary due to the lack of nursery teachers, and it will make an important progress on effective utilization of nursery teacher resources. In this paper, we proposed simultaneous children recognition and tracking system by using Kinect sensors for the childcare assisting system to provide information for the nursery teachers. Each of the children is recognized by integrating his/her personal information of color, face and motion. The tracking problem is modeled as finding the MAP solution of a posterior probability, and is solved by using Markov Chain Monte Carlo (MCMC) particle filter. Our system can recognize and robustly track each child during class activities. Trajectories, motion ranges and relative distances information can be provided for the nursery teachers to assist their childcare work. The effectiveness of our system is proved through continuous monitoring of the children in a nursery school.

Childcare Assisting System, Children Tracking, Children Recognition, MCMC Particle Filter

Zhang, B. , Nakamura, T. , Ushiogi, R. , Nagai, T. , Abe, K. , Omori, T. , Oka, N. and Kaneko, M. (2016) Simultaneous Children Recognition and Tracking for Childcare Assisting System by Using Kinect Sensors. Journal of Signal and Information Processing, 7, 148-159. doi: 10.4236/jsip.2016.73015.