Scaffolding on-line segmentation of full body human motion patterns

Dana Kulić, Yoshihiko Nakamura

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

31 Citations (Scopus)

Abstract

This paper develops an approach for on-line segmentation of whole body human motion patterns during human motion observation and learning. A Hidden Markov Model is used to represent the incoming data sequence, where each model state represents the probability density estimate over a window of the data. Based on the assumption that data belonging to the same motion primitive will have the same underlying distribution, the segmentation is implemented by finding the optimum state sequence over the developed model. The basic algorithm is modified to add the capability for modifying the model based on known motion primitives. The inclusion of such scaffolding motion primitives can improve the performance of the basic segmentation algorithm. The modified algorithm is tested on a corpus of continuous human motion data to show the efficacy of the proposed approach.

Original languageEnglish
Title of host publication2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages2860-2866
Number of pages7
ISBN (Print)9781424420582
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS - Nice, France
Duration: 22 Sep 200826 Sep 2008

Publication series

Name2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

Conference

Conference2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
CountryFrance
CityNice
Period22/09/0826/09/08

Cite this

Kulić, D., & Nakamura, Y. (2008). Scaffolding on-line segmentation of full body human motion patterns. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (pp. 2860-2866). [4650619] (2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IROS.2008.4650619