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          Institute: MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung)     Collection: Abt. Schölkopf (Empirical Inference)     Display Documents



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ID: 596834.0, MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung) / Abt. Schölkopf (Empirical Inference)
Movement extraction by detecting dynamics switches and repetitions
Authors:Chiappa, S.; Peters, J.
Publisher:Curran
Place of Publication:Red Hook, NY, USA
Date of Publication (YYYY-MM-DD):2011-06
Title of Proceedings:24th Annual Conference on Neural Information Processing Systems (NIPS 2010)
Start Page:388
End Page:396
Title of Series:Advances in Neural Information Processing Systems
Volume (in Series):23
Name of Conference/Meeting:24th Annual Conference on Neural Information Processing Systems (NIPS 2010
Place of Conference/Meeting:Vancouver, BC, Canada
(Start) Date of Conference/Meeting
 (YYYY-MM-DD):
2010-12-06
End Date of Conference/Meeting 
 (YYYY-MM-DD):
2010-12-09
Review Status:not specified
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:Many time-series such as human movement data consist of a sequence of basic actions, e.g., forehands and backhands in tennis. Automatically extracting and characterizing such actions is an important problem for a variety of different applications. In this paper, we present a probabilistic segmentation approach in which an observed time-series is modeled as a concatenation of segments corresponding
to different basic actions. Each segment is generated through a noisy transformation of one of a few hidden trajectories representing different types of movement,
with possible time re-scaling. We analyze three different approximation methods for dealing with model intractability, and demonstrate how the proposed approach
can successfully segment table tennis movements recorded using a robot arm as haptic input device.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Heide Klooz
Affiliations:MPI für Intelligente Systeme/Abt. Schölkopf
Identifiers:URL:http://www.kyb.tuebingen.mpg.de//fileadmin/user_up...
LOCALID:6742
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