A Real-Time Hand Gesture Recognition Approach Based on Motion Features of Feature Points

Dynamic hand gesture recognition enables people to communicate with computers naturally without any mechanical devices. Due to the spread of depth sensor such as Microsoft Kinect and Leap Motion, dynamic hand gesture recognition becomes possible for recognizing meticulous gesture information in real...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2014 IEEE 17th International Conference on Computational Science and Engineering s. 1096 - 1102
Hlavní autori: Yingying She, Qian Wang, Yunzhe Jia, Ting Gu, Qun He, Baorong Yang
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.12.2014
Predmet:
Classification algorithms
Feature extraction
feature points
Gesture recognition
hand gesture recognition
HCI
Joints
Labeling
motion feature
Thumb
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract Dynamic hand gesture recognition enables people to communicate with computers naturally without any mechanical devices. Due to the spread of depth sensor such as Microsoft Kinect and Leap Motion, dynamic hand gesture recognition becomes possible for recognizing meticulous gesture information in real time. However, most of these methods recognize the hand gesture by fuzzy features such as contour size, which cause imprecise hand gesture recognition. This paper presents a precise tracing of feature points including palm center, fingertips and joints by using Kinect. A novel recognition method based on precise motion features of these feature points is also presented. Having been tested with a series of applications, our method is proved to be robust and effective, and suitable for further application in real-time HCI systems.
AbstractList Dynamic hand gesture recognition enables people to communicate with computers naturally without any mechanical devices. Due to the spread of depth sensor such as Microsoft Kinect and Leap Motion, dynamic hand gesture recognition becomes possible for recognizing meticulous gesture information in real time. However, most of these methods recognize the hand gesture by fuzzy features such as contour size, which cause imprecise hand gesture recognition. This paper presents a precise tracing of feature points including palm center, fingertips and joints by using Kinect. A novel recognition method based on precise motion features of these feature points is also presented. Having been tested with a series of applications, our method is proved to be robust and effective, and suitable for further application in real-time HCI systems.
Author Yunzhe Jia
Qun He
Yingying She
Ting Gu
Qian Wang
Baorong Yang
Author_xml – sequence: 1
  surname: Yingying She
  fullname: Yingying She
  email: yingyingshe@xmu.edu.cn
  organization: Software Sch., Xiamen Univ., Xiamen, China
– sequence: 2
  surname: Qian Wang
  fullname: Qian Wang
  email: 740409563@qq.com
  organization: Software Sch., Xiamen Univ., Xiamen, China
– sequence: 3
  surname: Yunzhe Jia
  fullname: Yunzhe Jia
  email: 345019290@qq.com
  organization: Software Sch., Xiamen Univ., Xiamen, China
– sequence: 4
  surname: Ting Gu
  fullname: Ting Gu
  email: soliwly@qq.com
  organization: Software Sch., Xiamen Univ., Xiamen, China
– sequence: 5
  surname: Qun He
  fullname: Qun He
  email: 378343237@qq.com
  organization: Software Sch., Xiamen Univ., Xiamen, China
– sequence: 6
  surname: Baorong Yang
  fullname: Baorong Yang
  email: ybr@xmu.edu.cn
  organization: Software Sch., Xiamen Univ., Xiamen, China
BookMark eNo1jEtLw0AUhUdQ0Nbu3LmZP5A478cylj6EiqIV3JWbzI0OtJmQiQv_vfW1OofvO5wJOe1Sh4RccVZyzvzN_HlRCsZVKbg5IROurPfWO6bPySznWDNhrFHK2gvyWtEnhH2xjQeka-gCXWEePwY84ia9dXGMqaNV3w8Jmnd6CxkDPZL79COWCN_jTFP73-ljit2YL8lZC_uMs7-ckpflYjtfF5uH1d282hSRWz0WrQYhpEGsHZdBsBCYUqCUBCcVNth4Dg6MdNoG6ZiyUnuGtfSu1R5NLafk-vc3IuKuH-IBhs-dZUJaYeQXKMBPxg
CODEN IEEPAD
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CSE.2014.216
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 1479979805
9781479979813
1479979813
9781479979806
EndPage 1102
ExternalDocumentID 7023726
Genre orig-research
GroupedDBID 6IE
6IL
ALMA_UNASSIGNED_HOLDINGS
CBEJK
RIB
RIC
RIE
RIL
ID FETCH-LOGICAL-i175t-f5a2236eeb813d20dd044a443a834ecec91a8a63857d380473590eb398f59e6b3
IEDL.DBID RIE
ISICitedReferencesCount 13
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000380512100181&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Dec 20 05:19:03 EST 2023
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i175t-f5a2236eeb813d20dd044a443a834ecec91a8a63857d380473590eb398f59e6b3
PageCount 7
ParticipantIDs ieee_primary_7023726
PublicationCentury 2000
PublicationDate 2014-Dec.
PublicationDateYYYYMMDD 2014-12-01
PublicationDate_xml – month: 12
  year: 2014
  text: 2014-Dec.
PublicationDecade 2010
PublicationTitle 2014 IEEE 17th International Conference on Computational Science and Engineering
PublicationTitleAbbrev CSE
PublicationYear 2014
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssib026764477
Score 1.661438
Snippet Dynamic hand gesture recognition enables people to communicate with computers naturally without any mechanical devices. Due to the spread of depth sensor such...
SourceID ieee
SourceType Publisher
StartPage 1096
SubjectTerms Classification algorithms
Feature extraction
feature points
Gesture recognition
hand gesture recognition
HCI
Joints
Labeling
motion feature
Thumb
Title A Real-Time Hand Gesture Recognition Approach Based on Motion Features of Feature Points
URI https://ieeexplore.ieee.org/document/7023726
WOSCitedRecordID wos000380512100181&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV27bsIwFLUAdejUVlD1LQ8dawiOE9sjRVCGFiH6EBvy40ZiSSoS-v29Do926NLFsixLlu5NfPw4x4eQ-wxBRSVOMeGFDwVnlvuEZdybOEu0TWqV68eznE7VYqFnDfJw0MIAQE0-g26o1nf5vnCbcFTWkwgwkqdN0pQy3Wq19t8OTyUiu5QHbrvuDV9HgbolujyYmf_yTqmhY3zyv0FPSedHg0dnB3Q5Iw3I22QxoHNc2bEg3KATk3v6hLP6Zg10vicCFTkd7N4Jp48IUZ5iy0vt1UPDeg87l7TI9nU6K1Z5VXbI-3j0NpywnTcCWyHgVyxLDAJ7CmBVP_Y88j4SwggRGxULcOB03yiDP1cifayiYDCsI9w4a4UJgNTG56SVFzlcEKpckmkhUwvWYbKsNoji3GbWApaCX5J2iMryc_v8xXIXkKu_m6_JcQj6lvFxQ1rVegO35Mh9VatyfVfn7Bu4CJkG
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3NT8IwGMYbRBM9qQHjtz14dDC7dm2PSECMQAii4Uba9V3CZTMw_Pt9Oz704MVL0zRLlvTd9uu25-lDyH2KUFEiUQF33PmGBZY5EaTMmSgV2orS5frRl8Ohmk71qEIedl4YACjFZ9Dw3fJfvsuTlf9U1pQIGMniPbIvOGfh2q21vXpYLJHtUu7U7brZfut48RZvMB9n_is9pYRH9_h_pz0h9R8XHh3t-HJKKpDVyLRFx7i2C7x1g_ZM5ugzPtdXC6DjrRQoz2hrs1M4fUJIOYojgzKth_oVHx68pHm67dNRPs-KZZ28dzuTdi_YpCMEc0R-EaTCINpjAKseI8dC50LODeeRURGHBBL9aJTB20tIF6nQRwzrEF-dtcISQGyjM1LN8gzOCVWJSDWXsQWbYLmsNshxZlNrAVvOLkjNz8rsc70BxmwzIZd_D9-Rw95k0J_1X4avV-TIF2Ct_7gm1WKxghtykHwV8-XitqzfN914nE0
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2014+IEEE+17th+International+Conference+on+Computational+Science+and+Engineering&rft.atitle=A+Real-Time+Hand+Gesture+Recognition+Approach+Based+on+Motion+Features+of+Feature+Points&rft.au=Yingying+She&rft.au=Qian+Wang&rft.au=Yunzhe+Jia&rft.au=Ting+Gu&rft.date=2014-12-01&rft.pub=IEEE&rft.spage=1096&rft.epage=1102&rft_id=info:doi/10.1109%2FCSE.2014.216&rft.externalDocID=7023726