Beating-Time Gestures Imitation Learning for Humanoid Robots

Journal Title: EAI Endorsed Transactions on Creative Technologies - Year 2017, Vol 4, Issue 13

Abstract

Beating-time gestures are movement patterns of the hand swaying along with music, thereby indicating accented musical pulses. The spatiotemporal configuration of these patterns makes it diÿcult to analyse and model them. In this paper we present an innovative modelling approach that is based upon imitation learning or Programming by Demonstration (PbD). Our approach - based on Dirichlet Process Mixture Models, Hidden Markov Models, Dynamic Time Warping, and non-uniform cubic spline regression - is particularly innovative as it handles spatial and temporal variability by the generation of a generalised trajectory from a set of periodically repeated movements. Although not within the scope of our study, our procedures may be implemented for the sake of controlling movement behaviour of robots and avatar animations in response to music.

Authors and Affiliations

Denis Amelynck, Pieter-Jan Maes, Jean-Pierre Martens, Marc Leman

Keywords

Related Articles

Learnings from an Iterative Design Process for Technology-Mediated Audience Participation (TMAP) using Smartphones

We discuss a setup for technology-mediated audience participation (TMAP)in live music using smartphones and high-frequency sound IDs in a playful setting. The audience needs to install a smartphone app. Using high-freque...

A Multimodal Interaction Framework for Blended Learning

Humans interact with each other by utilizing the five basic senses as input modalities, whereas sounds, gestures, facial expressions etc. are utilized as output modalities. Multimodal interaction is also used between hum...

The A-Z of Creative Technologies

This paper undertakes an initial critical analysis of Creative Technologies as a means to gain insight to the nature of this as an emerging field. The paper utilises an approach previously used in the design discipline t...

Multi-GPU based framework for real-time motion analysis and tracking in multi-user scenarios

Video processing algorithms present a necessary tool for various domains related to computer vision such as motion tracking, event detection and localization in multi-user scenarios (crowd videos, mobile camera, scenes w...

Interactive Installations for Spatial Access to Artistic Sketchbooks

A book is a book – or is it? With present-day, a ordable technology, we can scale a book to become a spatial object, or even a space in itself, of almost arbitrary size. We describe our design of and experiences with a g...

Download PDF file
  • EP ID EP45882
  • DOI http://dx.doi.org/10.4108/eai.8-11-2017.153335
  • Views 291
  • Downloads 0

How To Cite

Denis Amelynck, Pieter-Jan Maes, Jean-Pierre Martens, Marc Leman (2017). Beating-Time Gestures Imitation Learning for Humanoid Robots. EAI Endorsed Transactions on Creative Technologies, 4(13), -. https://europub.co.uk/articles/-A-45882