@conference {
	title = {Learning Hand Movements from Markerless Demonstrations for Humanoid Tasks},
	author = {Mao, Ren., Yang, Yezhou., Fermuller, Cornelia., Aloimones, Yiannis., Baras, John S.},
	year = {2014},
	month = {11/2014},
	abstract = {We present a framework for generating trajectories of the hand movement during manipulation actions from demonstrations so the robot can perform similar actions in new situations. Our contribution is threefold: 1) we extract and transform hand movement trajectories using a state-of-the-art markerles full hand model tracker from Kinect sensor data; 2)we develop a new bio-inspired trajectory segmentation method that automatically segments complex movements into action units, and 3) we develop a generative method to learn task specific control using Dynamic Movement Primitives (DMPs).Experiments conducted both on synthetic data and real data using the Baxter research robot platform validate our approach.},
	address = {Madrid, Spain},
	booktitle = {2014 IEEE-RAS International Conference on Humanoid Robots (Humanoids 2014)},
	pages = {pp. 938-943}
}
