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Toshiro Mukai

dblp:48/1834 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 1999
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Human-computer interaction and ubiquitous computing · 1 · 1 first-author

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
Haptics and multimodal interaction · 50% Human-robot interaction · 25% User interface design and tools · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
User interface design and tools › interface models
dialogue model		 0.011999
Multimodal Agent Interface Based on Dynamical Dialogue Model · ACM Symposium on User Interface Software and Technology 1999
Human-robot interaction › robot communication
multimodal dialogue		 0.011999
Multimodal Agent Interface Based on Dynamical Dialogue Model · ACM Symposium on User Interface Software and Technology 1999
Haptics and multimodal interaction
multimodal interaction		 0.011999
Multimodal Agent Interface Based on Dynamical Dialogue Model · ACM Symposium on User Interface Software and Technology 1999
Haptics and multimodal interaction › multimodal interaction
speech and gesture interaction		 0.011999
Multimodal Agent Interface Based on Dynamical Dialogue Model · ACM Symposium on User Interface Software and Technology 1999

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

dialogue modeling · 0.0
YearPublicationVenuePosition
1999 Multimodal Agent Interface Based on Dynamical Dialogue Model
abstract
In this paper, we describe a multimodal interface prototype system based on Dynamical Dialogue Model. This system not only integrates information of speech and gestures, but also controls the response timing in order to realize a smooth interaction between user and computer. Our approach consists of human-human dialogue analysis, and computational modeling of dialogue.
Toshiro Mukai, Susumu Seki, Masayuki Nakazawa, Keiko Watanuki, Hideo Miyoshi
 ACM Symposium on User Interface Software and Technology1
1997 Spotting recognition of gestures performed by people from a single time-varying image
abstract
Our purpose is to recognize the human gestures from motion image without using contact type sensors such as data gloves or markers on hands. This paper proposes a method which can extracts good features from a small-sized image of a person and demonstrates the effectiveness using an omni-directional camera which can capture the gestures of more than one person.
Takuichi Nishimura, Toshiro Mukai
 IROS2