This paper presents a process to build a classifier in a datadriven way for recognizing engagement of children in a robotbased math quiz game. The process consists of collecting video recordings from HRI experiments; annotating the social signals and engagement states via video analysis; extracting feature vectors from the annotations and training classifiers. We conducted an experiment with 7 participants of 10 ∼ 11 years of age using an android robot EveR-4. With three coders annotating the video recordings and extracting features by snapshot model with 1-second time window, we achieved 84.83% recall performance.
Recently, interest of general public toward Ubiquitous Home Network has immensely increased and wireless PAN (Personal Area Network) has attracted strong attentions as short-distance networking solution. Convenience of Wireless PAN technology has attracted more attentions over traditional wired home network devices such as Ethernet, PLC and HomePNA since it requires no cabling work. In the future, home server will be combined with robot to provide functionalities identical to current home service robot as well as to implement more effective and spontaneous server. In this paper, embedded board has proposed as a home server for an efficient control of internal information and conditions of house from remote location and virtual home robot server to be implemented with Zigbee sensor network.
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