Painting Skill Transfer Through Haptic Channel
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Painting Skill Transfer Through Haptic Channel. / Raza, Ahsan; Abdullah, Muhammad; Hassan, Waseem; Abdulali, Arsen; Talhan, Aishwari; Jeon, Seokhee.
Haptic Interaction - Perception, Devices and Algorithms, 2018. ed. / Ki-Uk Kyung; Masashi Konyo; Hiroyuki Kajimoto; Dongjun Lee; Sang-Youn Kim. Springer Verlag, 2019. p. 66-68 (Lecture Notes in Electrical Engineering, Vol. 535).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Painting Skill Transfer Through Haptic Channel
AU - Raza, Ahsan
AU - Abdullah, Muhammad
AU - Hassan, Waseem
AU - Abdulali, Arsen
AU - Talhan, Aishwari
AU - Jeon, Seokhee
N1 - Funding Information: This research is supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program 2017. Funding Information: Acknowledgement. This research is supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program 2017. Publisher Copyright: © 2019, Springer Nature Singapore Pte Ltd.
PY - 2019
Y1 - 2019
N2 - In this paper, we focused on designing a system that can guide and train a user in painting an art work. Initially, we aim to develop a system which can guide a user with basic strokes of Korean language calligraphy. The proposed system is implemented in a sequence of three steps. Firstly, we collected the data from the surfaces of the canvas and different orientations of a painting brush. Then based on the data, a relationship is established among the collected parameters by building a machine learning model. Finally, actuators attached with the handle of the brush provides the vibrotactile and force feedback based on the built model. The actuator guides the user in order to paint the required object.
AB - In this paper, we focused on designing a system that can guide and train a user in painting an art work. Initially, we aim to develop a system which can guide a user with basic strokes of Korean language calligraphy. The proposed system is implemented in a sequence of three steps. Firstly, we collected the data from the surfaces of the canvas and different orientations of a painting brush. Then based on the data, a relationship is established among the collected parameters by building a machine learning model. Finally, actuators attached with the handle of the brush provides the vibrotactile and force feedback based on the built model. The actuator guides the user in order to paint the required object.
KW - Deep learning
KW - Haptic guidance
KW - Haptic painting
KW - Haptic rendering
KW - Painting skill
UR - http://www.scopus.com/inward/record.url?scp=85065957932&partnerID=8YFLogxK
U2 - 10.1007/978-981-13-3194-7_14
DO - 10.1007/978-981-13-3194-7_14
M3 - Article in proceedings
AN - SCOPUS:85065957932
SN - 9789811331930
T3 - Lecture Notes in Electrical Engineering
SP - 66
EP - 68
BT - Haptic Interaction - Perception, Devices and Algorithms, 2018
A2 - Kyung, Ki-Uk
A2 - Konyo, Masashi
A2 - Kajimoto, Hiroyuki
A2 - Lee, Dongjun
A2 - Kim, Sang-Youn
PB - Springer Verlag
T2 - 3rd International AsiaHaptics Conference, 2018
Y2 - 14 November 2018 through 16 November 2018
ER -
ID: 388953106