A bidirectional invariant representation of motion for gesture recognition and reproduction

Raffaele Soloperto, Matteo Saveriano, Dongheui Lee

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

12 Scopus citations

Abstract

Human action representation, recognition and learning is of importance to guarantee a fruitful human-robot cooperation. In this paper, we propose a novel coordinate-free, scale invariant representation of 6D (position and orientation) motion trajectories. The advantages of the proposed invariant representation are twofold. First the performance of gesture recognition can be improved thanks to its invariance to different viewpoints and different body sizes of the actors. Secondly, the proposed representation is bi-directional. Not only the original Cartesian trajectory can be converted into the 6 invariant values, but also the motion in the original space can be retrieved back from the invariants. While the former aspect handles robust human gesture recognition, the latter allows the execution of robot motions without the need to store the Cartesian data. Experimental results illustrate the effectiveness of the proposed invariant representation for gesture recognition and accurate trajectory reconstruction.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6146-6152
Number of pages7
EditionJune
ISBN (Electronic)9781479969234
DOIs
StatePublished - 29 Jun 2015
Externally publishedYes
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: 26 May 201530 May 2015

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
NumberJune
Volume2015-June
ISSN (Print)1050-4729

Conference

Conference2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Country/TerritoryUnited States
CitySeattle
Period26/05/1530/05/15

Fingerprint

Dive into the research topics of 'A bidirectional invariant representation of motion for gesture recognition and reproduction'. Together they form a unique fingerprint.

Cite this