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Tetsuya Tomonaka

dblp:74/3655 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments › context recognition
human behavior recognition
0.112006
Recognizing Human Behaviors with Vision Sensors in a Network Robot System · ICRA 2006

Methods — techniques the papers use, named apart from their topics

logical sensors · 0.1data fusion · 0.1
YearPublicationVenuePosition
2006 Recognizing Human Behaviors with Vision Sensors in a Network Robot System
abstract
A network robot system integrated with various types of robots via ubiquitous networks is a new concept which introduces an interactive robot living together with people. In this paper, we present a tangible network robot system composed of a mobile robot and vision sensors embedded in an environment, and show human behavior recognition methods necessary for providing diverse services desired by the people in good time. Typical human behaviors are described with logical sensors which are defined through data fusion processes spatially and temporally with the physical sensors of the mobile robot and those in the environment. Our system can be utilized to make human-robot communication and interaction friendlier and smarter
Keiichi Kemmotsu, Tetsuya Tomonaka, Shigetoshi Shiotani, Yoshihiro Koketsu, Masato Iehara
ICRA2