Style-based human motion segmentation

Yu Sheng, Amy Laviers

Research output: Contribution to journalConference articlepeer-review


This paper presents a method for segmenting human motion based on a notion of quality and the movement of a user such that the exact segmentation is tailored for different subjects. The problem is solved via an inverse optimal control problem where the parameter of optimization is a time along the movement trajectory that splits the longer trajectory into distinct "moves." First, trajectories are generated using a "forward" optimal control problem; then, the match of these generated trajectories is optimized via a second, "inverse" optimization, which determines the appropriate point of segmentation. An analytical solution to this set up, its numerical implementation, and an application to real data are presented. A key novel contribution of this paper is the analytical derivation of first order necessary conditions for optimality. The segmented movements may populate a library of movement primitives in order for robots and automated systems to perform and interpret novel tasks.

Original languageEnglish (US)
Article number6973914
Pages (from-to)240-245
Number of pages6
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Issue numberJanuary
StatePublished - Jan 1 2014
Externally publishedYes
Event2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States
Duration: Oct 5 2014Oct 8 2014

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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