TY - GEN
T1 - Finger identification and hand gesture recognition techniques for natural user interface
AU - Lee, Unseok
AU - Tanaka, Jiro
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - The natural user interface using hand gesture have been popular field in Human-Computer-Interaction(HCI). Many research papers have been proposed in this field. They proposed vision-based, glove-based and depth-based approach for hand gesture recognition. However, hand gesture itself is simple and not natural way to interact. In otherwise, hand gesture recognition using finger tracking and identification can be implemented more robust and subtle recognition. Recently, new horizons are open with the development of sensors and technology such as Kinect and Depth-Sense. This development has made possible robust recognition, like finger identification and hand gesture recognition in bad conditions such as dark light and rough background as well. In this paper, we proposed a new finger identification and hand gesture recognition techniques with kinect depth data. Our proposed finger identification and gesture recognition methods provide natural interactions and interface by using fingers. We implemented interfaces and designed hand gestures using this method. This paper explains finger identification method and hand gesture recognition in detail. We show the preliminary experiment for evaluating accuracy of finger identification and hand gesture recognition accuracy. Finally, we discuss the result of evaluation and our contributions.
AB - The natural user interface using hand gesture have been popular field in Human-Computer-Interaction(HCI). Many research papers have been proposed in this field. They proposed vision-based, glove-based and depth-based approach for hand gesture recognition. However, hand gesture itself is simple and not natural way to interact. In otherwise, hand gesture recognition using finger tracking and identification can be implemented more robust and subtle recognition. Recently, new horizons are open with the development of sensors and technology such as Kinect and Depth-Sense. This development has made possible robust recognition, like finger identification and hand gesture recognition in bad conditions such as dark light and rough background as well. In this paper, we proposed a new finger identification and hand gesture recognition techniques with kinect depth data. Our proposed finger identification and gesture recognition methods provide natural interactions and interface by using fingers. We implemented interfaces and designed hand gestures using this method. This paper explains finger identification method and hand gesture recognition in detail. We show the preliminary experiment for evaluating accuracy of finger identification and hand gesture recognition accuracy. Finally, we discuss the result of evaluation and our contributions.
KW - Finger identification
KW - Finger tracking
KW - Hand gesture recognition
KW - Human computer interaction
KW - Kinect
KW - Natural user interface
UR - http://www.scopus.com/inward/record.url?scp=84899824923&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84899824923&partnerID=8YFLogxK
U2 - 10.1145/2525194.2525296
DO - 10.1145/2525194.2525296
M3 - Conference contribution
AN - SCOPUS:84899824923
SN - 9781450322539
T3 - ACM International Conference Proceeding Series
SP - 274
EP - 279
BT - APCHI 2013 / India HCI 2013 - Joint Proceedings of the 11th Asia Pacific Conference on Computer Human Interaction and the 5th Indian Conference on Human Computer Interaction
PB - Association for Computing Machinery
T2 - Joint 11th Asia Pacific Conference on Computer Human Interaction, APCHI 2013 and the 5th Indian Conference on Human Computer Interaction, India HCI 2013
Y2 - 24 September 2013 through 27 September 2013
ER -