HCI based on gesture recognition in an augmented reality system for diagnosis planning and training

Qiming Li; Chen Huang; Zeyu Li; Yimin Chen; Lizhuang Ma

doi:10.1007/978-3-319-68121-4_12

HCI based on gesture recognition in an augmented reality system for diagnosis planning and training

Qiming Li^*
, Chen Huang
, Zeyu Li
, Yimin Chen
, Lizhuang Ma

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

An Augmented Reality System for Coronary Artery Diagnosis Planning and Training (ARS-CADPT) is designed and realized in this paper. As the characteristic of ARS-CADPT, the algorithms of static gesture recognition and dynamic gesture spotting and recognition are presented to realize the real-time and friendly Human-Computer Interaction (HCI). The experimental results show that, with the use of ARS-CADPT, the HCI is natural and fluent, which improves the user’s immersion and improves the diagnosis and training effects.

Original language	English
Title of host publication	Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings
Editors	Zhongzhi Shi, Ben Goertzel, Jiali Feng
Publisher	Springer New York LLC
Pages	113-123
Number of pages	11
ISBN (Print)	9783319681207
DOIs	https://doi.org/10.1007/978-3-319-68121-4_12
State	Published - 2017
Externally published	Yes
Event	2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017 - Shanghai, China Duration: 25 Oct 2017 → 28 Oct 2017

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	510
ISSN (Print)	1868-4238

Conference

Conference	2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017
Country/Territory	China
City	Shanghai
Period	25/10/17 → 28/10/17

Keywords

Augmented reality
Gesture recognition
Human computer interaction

Access to Document

10.1007/978-3-319-68121-4_12

Cite this

Li, Q., Huang, C., Li, Z., Chen, Y., & Ma, L. (2017). HCI based on gesture recognition in an augmented reality system for diagnosis planning and training. In Z. Shi, B. Goertzel, & J. Feng (Eds.), Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings (pp. 113-123). (IFIP Advances in Information and Communication Technology; Vol. 510). Springer New York LLC. https://doi.org/10.1007/978-3-319-68121-4_12

Li, Qiming ; Huang, Chen ; Li, Zeyu et al. / HCI based on gesture recognition in an augmented reality system for diagnosis planning and training. Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings. editor / Zhongzhi Shi ; Ben Goertzel ; Jiali Feng. Springer New York LLC, 2017. pp. 113-123 (IFIP Advances in Information and Communication Technology).

@inproceedings{7c1cdba9baf74bbba29e218d4200c00f,

title = "HCI based on gesture recognition in an augmented reality system for diagnosis planning and training",

abstract = "An Augmented Reality System for Coronary Artery Diagnosis Planning and Training (ARS-CADPT) is designed and realized in this paper. As the characteristic of ARS-CADPT, the algorithms of static gesture recognition and dynamic gesture spotting and recognition are presented to realize the real-time and friendly Human-Computer Interaction (HCI). The experimental results show that, with the use of ARS-CADPT, the HCI is natural and fluent, which improves the user{\textquoteright}s immersion and improves the diagnosis and training effects.",

keywords = "Augmented reality, Gesture recognition, Human computer interaction",

author = "Qiming Li and Chen Huang and Zeyu Li and Yimin Chen and Lizhuang Ma",

note = "Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2017.; 2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017 ; Conference date: 25-10-2017 Through 28-10-2017",

year = "2017",

doi = "10.1007/978-3-319-68121-4\_12",

language = "英语",

isbn = "9783319681207",

series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer New York LLC",

pages = "113--123",

editor = "Zhongzhi Shi and Ben Goertzel and Jiali Feng",

booktitle = "Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings",

}

Li, Q, Huang, C, Li, Z, Chen, Y & Ma, L 2017, HCI based on gesture recognition in an augmented reality system for diagnosis planning and training. in Z Shi, B Goertzel & J Feng (eds), Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings. IFIP Advances in Information and Communication Technology, vol. 510, Springer New York LLC, pp. 113-123, 2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017, Shanghai, China, 25/10/17. https://doi.org/10.1007/978-3-319-68121-4_12

HCI based on gesture recognition in an augmented reality system for diagnosis planning and training. / Li, Qiming; Huang, Chen; Li, Zeyu et al.
Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings. ed. / Zhongzhi Shi; Ben Goertzel; Jiali Feng. Springer New York LLC, 2017. p. 113-123 (IFIP Advances in Information and Communication Technology; Vol. 510).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - HCI based on gesture recognition in an augmented reality system for diagnosis planning and training

AU - Li, Qiming

AU - Huang, Chen

AU - Li, Zeyu

AU - Chen, Yimin

AU - Ma, Lizhuang

N1 - Publisher Copyright: © IFIP International Federation for Information Processing 2017.

PY - 2017

Y1 - 2017

N2 - An Augmented Reality System for Coronary Artery Diagnosis Planning and Training (ARS-CADPT) is designed and realized in this paper. As the characteristic of ARS-CADPT, the algorithms of static gesture recognition and dynamic gesture spotting and recognition are presented to realize the real-time and friendly Human-Computer Interaction (HCI). The experimental results show that, with the use of ARS-CADPT, the HCI is natural and fluent, which improves the user’s immersion and improves the diagnosis and training effects.

AB - An Augmented Reality System for Coronary Artery Diagnosis Planning and Training (ARS-CADPT) is designed and realized in this paper. As the characteristic of ARS-CADPT, the algorithms of static gesture recognition and dynamic gesture spotting and recognition are presented to realize the real-time and friendly Human-Computer Interaction (HCI). The experimental results show that, with the use of ARS-CADPT, the HCI is natural and fluent, which improves the user’s immersion and improves the diagnosis and training effects.

KW - Augmented reality

KW - Gesture recognition

KW - Human computer interaction

UR - https://www.scopus.com/pages/publications/85032690247

U2 - 10.1007/978-3-319-68121-4_12

DO - 10.1007/978-3-319-68121-4_12

M3 - 会议稿件

AN - SCOPUS:85032690247

SN - 9783319681207

T3 - IFIP Advances in Information and Communication Technology

SP - 113

EP - 123

BT - Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings

A2 - Shi, Zhongzhi

A2 - Goertzel, Ben

A2 - Feng, Jiali

PB - Springer New York LLC

T2 - 2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017

Y2 - 25 October 2017 through 28 October 2017

ER -

Li Q, Huang C, Li Z, Chen Y, Ma L. HCI based on gesture recognition in an augmented reality system for diagnosis planning and training. In Shi Z, Goertzel B, Feng J, editors, Intelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings. Springer New York LLC. 2017. p. 113-123. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-319-68121-4_12

HCI based on gesture recognition in an augmented reality system for diagnosis planning and training

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Keywords

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