Responsive-ExtendedHand: Adaptive Visuo-Haptic Feedback Recognizing Object Property With RGB-D Camera for Projected Extended Hand

Sato, Yushi; Iwai, Daisuke; Sato, Kosuke

IEEE Access, 2024, 12, 38247-38257

アクセス数:410件（2025-07-27 13:32 集計）

固定URL: https://hdl.handle.net/11094/95647

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論文情報

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タイトル
Responsive-ExtendedHand: Adaptive Visuo-Haptic Feedback Recognizing Object Property With RGB-D Camera for Projected Extended Hand
著者
著者名
Sato, Yushi
NRID
1000090504837 1000090504837
researchmap permalink
daisukeiwai daisukeiwai
Scopus Author ID
55931917600 55931917600
著者名
Iwai, Daisuke
NRID
1000090187188 1000090187188
researchmap permalink
read0076311 read0076311
Scopus Author ID
56192879500 56192879500
著者名
Sato, Kosuke
キーワード等
Augmented reality
body augmentation
deep neural network
pseudo-haptics
内容
Sato Y., Iwai D., Sato K.. Responsive-ExtendedHand: Adaptive Visuo-Haptic Feedback Recognizing Object Property With RGB-D Camera for Projected Extended Hand. IEEE Access 12, 38247 (2024); https://doi.org/10.1109/ACCESS.2024.3375917.
抄録
The ExtendedHand interface displays computer graphics (CG) hand images in real space from a projector, allowing the user to visually point at and touch real objects that are out of their physical reach. Furthermore, when the projected CG hand (extended hand) touches an object, the user can feel the tactile sensation of the object through pseudo-haptics by giving the extended hand visual effects that emphasize the action. In the previous psychological study, the human operator had to manually assign the location and shape of objects and the intensities of their visual effects in advance in order to emphasize the appropriate visual effect for the object touched by the extended hand. To increase practical feasibility, we propose an adaptive system that utilizes an RGB-D camera and deep neural networks to generate the appropriate visual effects automatically and apply them to the projected extended hand. By employing U-Net to generate the appropriate intensities of the visual effects from the captured color and depth images, the system can estimate the appropriate visual effects for objects without pre-setting them. The user evaluation results showed that the proposed system allowed users to naturally perceive the tactile sensation of objects at a rate of 44%, instead of the manual rate of 49%.
出版者
Institute of Electrical and Electronics Engineers Inc.
収録物名
IEEE Access
巻(号)
12
ページ
38247-38257
刊行年月
2024-03-15
言語
英語
ハンドルURL
https://hdl.handle.net/11094/95647
eISSN
21693536
関連情報 (isIdenticalTo)
DOI (出版社版)
https://doi.org/10.1109/ACCESS.2024.3375917
アクセス権
open access
権利情報
This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ
Version of Record
カテゴリ
学術雑誌論文 Journal Article