Coherence in One-Shot Gesture Recognition for Human-Robot Interaction

  • Maria E. Cabrera
  • , Richard M. Voyles
  • , Juan P. Wachs

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

Abstract

An experiment was conducted where a robotic platform performs artificially generated gestures and both trained classifiers and human participants recognize. Classification accuracy is evaluated through a new metric of coherence in gesture recognition between humans and robots. Experimental results showed an average recognition performance of 89.2% for the trained classifiers and 92.5% for the participants. Coherence in one-shot gesture recognition was determined to be gamma = 93.8%. This new metric provides a quantifier for validating how realistic the robotic generated gestures are.

Original languageEnglish
Title of host publicationHRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction
PublisherInstitute of Electrical and Electronics Engineers
Pages75-76
Number of pages2
ISBN (Electronic)9781450356152
DOIs
StatePublished - 1 Mar 2018
Externally publishedYes
Event13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018 - Chicago, United States
Duration: 5 Mar 20188 Mar 2018

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018
Country/TerritoryUnited States
CityChicago
Period5/03/188/03/18

Keywords

  • gesture recognition
  • one-shot learning
  • robotics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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