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Yoshihiko Sugawara

dblp:10/563 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 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.

Computer graphics and multimedia
2 papers
Virtual and augmented reality · 100%
Human-computer interaction and pervasive computing
1 paper
Immersive interaction · 100%
Artificial intelligence
1 paper
3D vision · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality
augmented reality		 0.122000
Accurate Image Overlay on Video See-through HMDs Using Vision and Accelerometers · VR 2000
Accurate Image Overlay on Head-Mounted Displays Using Vision and Accelerometers · ICRA 1999
Virtual and augmented reality › augmented reality
image overlay		 0.122000
Accurate Image Overlay on Video See-through HMDs Using Vision and Accelerometers · VR 2000
Accurate Image Overlay on Head-Mounted Displays Using Vision and Accelerometers · ICRA 1999
Immersive interaction
head-mounted display		 0.012000
Accurate Image Overlay on Video See-through HMDs Using Vision and Accelerometers · VR 2000

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

vision-based tracking · 0.1accelerometer-based motion prediction · 0.1head motion prediction · 0.0accelerometer fusion · 0.0
YearPublicationVenuePosition
2001 Mechano-Media that Transmit Kinesthetic Knowledge from a Human to Other Humans
Yasuyoshi Yokokohji, Yoshihiko Sugawara, Junji Kinoshita, Tsuneo Yoshikawa
 ISRR2
2000 Accurate Image Overlay on Video See-through HMDs Using Vision and Accelerometers
abstract
Proposes a method for accurate image overlay on head-mounted displays (HMDs) using vision and accelerometers. The proposed method is suitable for video see-through HMDs in augmented reality applications but is not limited to them. Acceleration information is used for predicting the head motion to compensate the end-to-end system delay and to make the vision-based tracking robust. Experimental results showed that the proposed method can reduce the alignment errors within 6 pixels on average and 11 pixels at the maximum, even is the user moves his/her head quickly (with 10 m/s/sup 2/ and 49 rad/s/sup 2/ at the maximum). The viewing range was enlarged by placing additional landmarks in the environment.
Yasuyoshi Yokokohji, Yoshihiko Sugawara, Tsuneo Yoshikawa
 VR2
1999 Accurate Image Overlay on Head-Mounted Displays Using Vision and Accelerometers
abstract
We propose a method for accurate image overlay on head-mounted displays (HMDs) using vision and accelerometers. The proposed method is suitable for video see-through HMDs in, augmented reality applications but not limited to them. Acceleration information is used for predicting the head motion to compensate the end-to-end system delay and to make the vision-based tracking robust. Experimental results showed that the proposed method can reduce the alignment errors within 6 pixels on average and 11 pixels at the maximum, even if the user moves his/her head quickly (with 10 [m/s/sup 2/] and 49 [rad/s/sup 2/] at the maximum).
Yasuyoshi Yokokohji, Yoshihiko Sugawara, Tsuneo Yoshikawa
 ICRA2