Tracking the path shape qualities of human motion

Kai Tu, Harvey Thornburg, Matthew Fulmer, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We propose a probabilistic generative model for extracting intended path shape qualities of an object moving under human control in real time. At each instant, we decide whether the object is moving in a straight, curved, or random path, or whether it has stopped moving. Our model incorporates sensor noise as well as human imperfections in the intended motion. As well as tracking the object's position, velocity, and motion direction, we compute the posterior probability of each shape quality hypothesis given all sensed-data in the horizon [t -N + 1, t]; the hypothesis maximizing this posterior is taken as the decision. The posterior is computed using the unscented Kaiman filter (UKF), as our model is inherently nonlinear. The path-shape quality tracking is successfully embedded in a hybrid physical-digital interface where the position of an illuminated ball, sensed by a low-cost video camera array, triggers multimodal feedback in a mediated learning environment. We show successful results on a variety of real-world motion paths where the participant is given only verbal descriptions of how to move. Our generative model is further validated by user studies involving a simple color-based interaction, where participants discover shape quality controls as they interact.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PagesII781-II784
DOIs
StatePublished - Aug 6 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: Apr 15 2007Apr 20 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Other

Other2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
CountryUnited States
CityHonolulu, HI
Period4/15/074/20/07

Keywords

  • Activity analysis
  • Computer vision
  • Human motion analysis
  • Human-computer interaction
  • Hybrid physical-digital environment
  • Multimedia signal processing
  • Natural information interface
  • Unscented Kalman filter
  • Video sensing

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Tu, K., Thornburg, H., Fulmer, M., & Spanias, A. (2007). Tracking the path shape qualities of human motion. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 (pp. II781-II784). [4217525] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2). https://doi.org/10.1109/ICASSP.2007.366352