Multiple Children Identification and Tracking for the Childcare Assisting System
Bin Zhang, Tomoaki Nakamura, Takayuki Nagai, Takashi Omori, Masahide Kaneko, Haibin Xia, Rena Ushiogi, Natsuki Oka, Hun‐ok Lim · 2019
To improve the quality of childcare in nursery schools by using information technologies, a childcare assisting system is proposed to help the teachers with their daily works. The first step of the system is automatically monitoring and analyzing the behaviors of the children. In this paper, a multiple children identification and tracking method is proposed by using color and depth information from the sensors setting in the environment. The children are identified by integrating multiple personal information of color, face, moving pattern, and the identification results are used as the observation likelihoods in the particle filter based tracking process. The proposed method can continuously track multiple children under complex environment with occlusions among children and fast motions crossing with each other. The effectiveness of the proposed method is proven by the experiments conducted in a nursery school.