Robust Children Behavior Tracking for Childcare Assisting Robot by Using Multiple Kinect Sensors View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Bin Zhang , Tomoaki Nakamura , Rena Ushiogi , Takayuki Nagai , Kasumi Abe , Takashi Omori , Natsuki Oka , Masahide Kaneko

ABSTRACT

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. More... »

PAGES

640-649

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-47437-3_63

DOI

http://dx.doi.org/10.1007/978-3-319-47437-3_63

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038113655


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