TY - GEN
T1 - Gesture imitation using machine learning techniques
AU - Itauma, Itauma Isong
AU - Kivrak, Hasan
AU - Kose, Hatice
PY - 2012
Y1 - 2012
N2 - This study is a part of an ongoing project which aims to assist in teaching Sign Language (SL) to hearing-impaired children by means of non-verbal communication and imitation-based interaction games between a humanoid robot and a child. In this paper, the problem is geared towards a robot learning to imitate basic upper torso gestures (SL signs) using different machine learning techniques. RGBD sensor (Microsoft Kinect) is employed to track the skeletal model of humans and create a training set. A novel method called Decision Based Rule is proposed. Additionally, linear regression models are compared to find which learning technique has a higher accuracy on gesture prediction. The learning technique with the highest accuracy is then used to simulate an imitation system where the Nao robot imitates these learned gestures as observed by the users.
AB - This study is a part of an ongoing project which aims to assist in teaching Sign Language (SL) to hearing-impaired children by means of non-verbal communication and imitation-based interaction games between a humanoid robot and a child. In this paper, the problem is geared towards a robot learning to imitate basic upper torso gestures (SL signs) using different machine learning techniques. RGBD sensor (Microsoft Kinect) is employed to track the skeletal model of humans and create a training set. A novel method called Decision Based Rule is proposed. Additionally, linear regression models are compared to find which learning technique has a higher accuracy on gesture prediction. The learning technique with the highest accuracy is then used to simulate an imitation system where the Nao robot imitates these learned gestures as observed by the users.
UR - http://www.scopus.com/inward/record.url?scp=84863490294&partnerID=8YFLogxK
U2 - 10.1109/SIU.2012.6204822
DO - 10.1109/SIU.2012.6204822
M3 - Conference contribution
AN - SCOPUS:84863490294
SN - 9781467300568
T3 - 2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
BT - 2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
T2 - 2012 20th Signal Processing and Communications Applications Conference, SIU 2012
Y2 - 18 April 2012 through 20 April 2012
ER -