TY - GEN
T1 - A real-time hand gesture recognition algorithm for an embedded system
AU - Lei, You
AU - Hongpeng, Wang
AU - Dianxiong, Tan
AU - Jue, Wang
PY - 2014
Y1 - 2014
N2 - With the development of technology, intelligent robots will play an important role in our daily life. More and more intelligent robots based on embedded systems are used for security, detection, service, etc. Interaction with human is an important part of intelligent robots. Hand gesture is a convenient and fast method for human-robot interactions. In this paper, we propose a method which is suitable to detect hand area and recognize hand gestures for video stream on an embedded system. In order to make the recognition process run in real-time, the proposed method is based on Gaussian Mixture Model (GMM) which not only helps to build the skin model but also helps to classify the gestures. An embedded system with our algorithm is almost the same with a PC(Intel Core i3 500, 4G DDR3) real-time performance. At the same time, the average recognition rate is more than 75%. Both the embedded system and the real time hand gesture recognition algorithm is used to control an intelligent robot.
AB - With the development of technology, intelligent robots will play an important role in our daily life. More and more intelligent robots based on embedded systems are used for security, detection, service, etc. Interaction with human is an important part of intelligent robots. Hand gesture is a convenient and fast method for human-robot interactions. In this paper, we propose a method which is suitable to detect hand area and recognize hand gestures for video stream on an embedded system. In order to make the recognition process run in real-time, the proposed method is based on Gaussian Mixture Model (GMM) which not only helps to build the skin model but also helps to classify the gestures. An embedded system with our algorithm is almost the same with a PC(Intel Core i3 500, 4G DDR3) real-time performance. At the same time, the average recognition rate is more than 75%. Both the embedded system and the real time hand gesture recognition algorithm is used to control an intelligent robot.
KW - Gaussian mixture model
KW - embedded system
KW - hand gesture recognition
UR - https://www.scopus.com/pages/publications/84906987354
U2 - 10.1109/ICMA.2014.6885817
DO - 10.1109/ICMA.2014.6885817
M3 - 会议稿件
AN - SCOPUS:84906987354
SN - 9781479939787
T3 - 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
SP - 901
EP - 905
BT - 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
PB - IEEE Computer Society
T2 - 11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
Y2 - 3 August 2014 through 6 August 2014
ER -