Painting Skill Transfer Through Haptic Channel

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Standard

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. red. / Ki-Uk Kyung; Masashi Konyo; Hiroyuki Kajimoto; Dongjun Lee; Sang-Youn Kim. Springer Verlag, 2019. s. 66-68 (Lecture Notes in Electrical Engineering, Bind 535).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Harvard

Raza, A, Abdullah, M, Hassan, W, Abdulali, A, Talhan, A & Jeon, S 2019, Painting Skill Transfer Through Haptic Channel. i K-U Kyung, M Konyo, H Kajimoto, D Lee & S-Y Kim (red), Haptic Interaction - Perception, Devices and Algorithms, 2018. Springer Verlag, Lecture Notes in Electrical Engineering, bind 535, s. 66-68, 3rd International AsiaHaptics Conference, 2018, Incheon, Sydkorea, 14/11/2018. https://doi.org/10.1007/978-981-13-3194-7_14

APA

Raza, A., Abdullah, M., Hassan, W., Abdulali, A., Talhan, A., & Jeon, S. (2019). Painting Skill Transfer Through Haptic Channel. I K-U. Kyung, M. Konyo, H. Kajimoto, D. Lee, & S-Y. Kim (red.), Haptic Interaction - Perception, Devices and Algorithms, 2018 (s. 66-68). Springer Verlag. Lecture Notes in Electrical Engineering Bind 535 https://doi.org/10.1007/978-981-13-3194-7_14

Vancouver

Raza A, Abdullah M, Hassan W, Abdulali A, Talhan A, Jeon S. Painting Skill Transfer Through Haptic Channel. I Kyung K-U, Konyo M, Kajimoto H, Lee D, Kim S-Y, red., Haptic Interaction - Perception, Devices and Algorithms, 2018. Springer Verlag. 2019. s. 66-68. (Lecture Notes in Electrical Engineering, Bind 535). https://doi.org/10.1007/978-981-13-3194-7_14

Author

Raza, Ahsan ; Abdullah, Muhammad ; Hassan, Waseem ; Abdulali, Arsen ; Talhan, Aishwari ; Jeon, Seokhee. / Painting Skill Transfer Through Haptic Channel. Haptic Interaction - Perception, Devices and Algorithms, 2018. red. / Ki-Uk Kyung ; Masashi Konyo ; Hiroyuki Kajimoto ; Dongjun Lee ; Sang-Youn Kim. Springer Verlag, 2019. s. 66-68 (Lecture Notes in Electrical Engineering, Bind 535).

Bibtex

@inproceedings{830b26a2f124466fb1cb25d124e1bc92,
title = "Painting Skill Transfer Through Haptic Channel",
abstract = "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.",
keywords = "Deep learning, Haptic guidance, Haptic painting, Haptic rendering, Painting skill",
author = "Ahsan Raza and Muhammad Abdullah and Waseem Hassan and Arsen Abdulali and Aishwari Talhan and Seokhee Jeon",
note = "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: {\textcopyright} 2019, Springer Nature Singapore Pte Ltd.; 3rd International AsiaHaptics Conference, 2018 ; Conference date: 14-11-2018 Through 16-11-2018",
year = "2019",
doi = "10.1007/978-981-13-3194-7_14",
language = "English",
isbn = "9789811331930",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "66--68",
editor = "Ki-Uk Kyung and Masashi Konyo and Hiroyuki Kajimoto and Dongjun Lee and Sang-Youn Kim",
booktitle = "Haptic Interaction - Perception, Devices and Algorithms, 2018",
address = "Germany",

}

RIS

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