Abstract
This paper proposes a robot control human interface using Markov model (HMM) based hand signal recognizer. The command receiving humanoid robot sends webcam images to a client computer. The client computer then extracts the intended commanding human's hand motion descriptors. Upon the feature acquisition, the hand signal recognizer carries out the recognition procedure. The recognition result is then sent back to the robot for responsive actions. The system performance is evaluated by measuring the recognition of '48 hand signal set' which is created randomly using fundamental hand motion set. For isolated motion recognition, '48 hand signal set' shows 97.07% recognition rate while the 'baseline hand signal set' shows 92.4%. This result validates the proposed hand signal recognizer is indeed highly discernable. For the '48 hand signal set' connected motions, it shows 97.37% recognition rate. The relevant experiments demonstrate that the proposed system is promising for real world human-robot interface application.
| Original language | English |
|---|---|
| Pages (from-to) | 368-374 |
| Number of pages | 7 |
| Journal | Journal of Institute of Control, Robotics and Systems |
| Volume | 17 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2011 Apr 1 |
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Keywords
- Hand gesture
- HMM
- Robot control system
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Applied Mathematics
Cite this
Robot user control system using hand gesture recognizer. / Shon, Suwon; Beh, Jounghoon; Yang, Cheoljong; Wang, Han; Ko, Hanseok.
In: Journal of Institute of Control, Robotics and Systems, Vol. 17, No. 4, 01.04.2011, p. 368-374.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Robot user control system using hand gesture recognizer
AU - Shon, Suwon
AU - Beh, Jounghoon
AU - Yang, Cheoljong
AU - Wang, Han
AU - Ko, Hanseok
PY - 2011/4/1
Y1 - 2011/4/1
N2 - This paper proposes a robot control human interface using Markov model (HMM) based hand signal recognizer. The command receiving humanoid robot sends webcam images to a client computer. The client computer then extracts the intended commanding human's hand motion descriptors. Upon the feature acquisition, the hand signal recognizer carries out the recognition procedure. The recognition result is then sent back to the robot for responsive actions. The system performance is evaluated by measuring the recognition of '48 hand signal set' which is created randomly using fundamental hand motion set. For isolated motion recognition, '48 hand signal set' shows 97.07% recognition rate while the 'baseline hand signal set' shows 92.4%. This result validates the proposed hand signal recognizer is indeed highly discernable. For the '48 hand signal set' connected motions, it shows 97.37% recognition rate. The relevant experiments demonstrate that the proposed system is promising for real world human-robot interface application.
AB - This paper proposes a robot control human interface using Markov model (HMM) based hand signal recognizer. The command receiving humanoid robot sends webcam images to a client computer. The client computer then extracts the intended commanding human's hand motion descriptors. Upon the feature acquisition, the hand signal recognizer carries out the recognition procedure. The recognition result is then sent back to the robot for responsive actions. The system performance is evaluated by measuring the recognition of '48 hand signal set' which is created randomly using fundamental hand motion set. For isolated motion recognition, '48 hand signal set' shows 97.07% recognition rate while the 'baseline hand signal set' shows 92.4%. This result validates the proposed hand signal recognizer is indeed highly discernable. For the '48 hand signal set' connected motions, it shows 97.37% recognition rate. The relevant experiments demonstrate that the proposed system is promising for real world human-robot interface application.
KW - Hand gesture
KW - HMM
KW - Robot control system
UR - http://www.scopus.com/inward/record.url?scp=79960944461&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960944461&partnerID=8YFLogxK
U2 - 10.5302/J.ICROS.2011.17.4.368
DO - 10.5302/J.ICROS.2011.17.4.368
M3 - Article
AN - SCOPUS:79960944461
VL - 17
SP - 368
EP - 374
JO - Journal of Institute of Control, Robotics and Systems
JF - Journal of Institute of Control, Robotics and Systems
SN - 1976-5622
IS - 4
ER -