NDLI: Detecting dance motion structure using body components and turning motions

Content Provider	IEEE Xplore Digital Library
Author	Rennhak, B. Shiratori, T. Kudoh, S. Vinayavekhin, P. Ikeuchi, K.
Copyright Year	2010
Description	Author affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505 JAPAN (Rennhak, B.; Kudoh, S.; Vinayavekhin, P.; Ikeuchi, K.) \|\| The Robotics Institute, Carnegie Mellon University, 4615 Forbes Avenue, Suite 420, Pittsburgh, 15213 USA (Shiratori, T.)
Abstract	This paper presents a novel method for robust dance motion structure detection. In the japanese folk dance domain, teachers created illustrations of dance poses. These poses characterize the most important movements of a dance. So far there is no simple and reliable extraction method which can extract all poses as shown in these drawings. We use these poses for the Task Model (TM) in the context of Learning from Observation (LFO). LFO which is a well known technique for successful human to robot motion mapping, consists of tasks (what to do) and skills (how to do). We propose a novel approach, to extract special motions from a dance, called turning motions useful for skill mapping in the LFO paradigm. Furthermore, we use a modified version of this approach, to detect all poses as shown in the drawings, called turning poses. To achieve this we observe both forearms at the same time and analyze their movement in different 2-D coordinate planes. We evaluate the parameters with and without a weighting function where we minimize acceleration, velocity and power. We successfully demonstrate this novel method using two very different japanese folk dances and discuss further implications of this work in respect to the LFO paradigm and dances of other domains.
Starting Page	2264
Ending Page	2269
File Size	1414917
Page Count	6
File Format	PDF
ISBN	9781424466740
ISSN	21530866
e-ISBN	9781424466764
DOI	10.1109/IROS.2010.5649303
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Turning Manganese Humans Robots Trajectory Dynamics Mathematical model
Content Type	Text
Resource Type	Article

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