Kosuke Sato
Osaka University
218 Papers
791 Citations
Kosuke Sato is an academic researcher from Osaka University. The author has contributed to research in topics: Projector & Computer science. The author has an hindex of 18, co-authored 200 publications. Previous affiliations of Kosuke Sato include National Archives and Records Administration & National Presto Industries.
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Papers
SoftAR : Visually Manipulating Haptic Softness Perception in Spatial Augmented Reality
TL;DR: Through psychophysical experiments, it is confirmed that the SDE can manipulate softness perception such that the participant perceives significantly greater softness than the actual softness.
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Real-time gesture recognition by learning and selective control of visual interest points
TL;DR: This paper developed a selective control method to equip the recognition system with self-load monitoring and controlling functionality, and shows that the approach provides robust recognition with respect to such factors as type of clothing, type of gesture, extent of motion trajectories, and individual differences in motion characteristics.
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Some further results of experimental comparison of range image segmentation algorithms
Xiaoyi Jiang,Kevin W. Bowyer,Y. Morioka,Shinsaku Hiura,Kosuke Sato,Seiji Inokuchi,M. Bock,C. Guerra,R.E. Loke,J. M. H. du Buf +9 more
- 03 Sep 2000
TL;DR: A range image segmentation contest was organized in conjunction with ICPR'2000 and the goal is to continue the effort of experimentally evaluating range image segmentsation algorithms initiated by Hoover et al. (1996) and Powell et al (1998).
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A wearable mixed reality with an on-board projector
Toshikazu Karitsuka,Kosuke Sato +1 more
- 07 Oct 2003
TL;DR: This demonstration proposes a wearable MR system with an on-board projector and introduces some applications with this system, which can get the same MR environments without using HMD at the same moment.
FoodFab: Creating Food Perception Illusions using Food 3D Printing
Ying-Ju Lin,Parinya Punpongsanon,Xin Wen,Daisuke Iwai,Kosuke Sato,Marianna Obrist,Stefanie Mueller +6 more
- 21 Apr 2020
TL;DR: This paper presents FoodFab, a system that allows users to control their food intake through modifying a food's internal structure via two 3D printing parameters: infill pattern and infill density, and proposes two computational models that integrate them into a user interface that simplifies the creation of personalized food structures.
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