Weighting observations: The use of kinematic models in object tracking

K. Nickels, S. Hutchinson

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

Abstract

We describe a model-based object tracking system that updates the configuration parameters of an object model based upon information gathered from a sequence of monocular images. Realistic object and imaging models are used to determine the expected visibility of object features, and to determine the expected appearance of all visible features. We formulate the tracking problem as one of parameter estimation from partially observed data, and apply the extended Kalman filtering (EKF) algorithm. The models are also used to determine what point feature movement reveals about the configuration parameters of the object. This information is used by the EKF to update estimates for parameters, and for the uncertainty in the current estimates, based on observations of point features in monocular images.

Original languageEnglish (US)
Title of host publicationProceedings - 1998 IEEE International Conference on Robotics and Automation, ICRA 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1677-1682
Number of pages6
ISBN (Print)078034300X
DOIs
StatePublished - 1998
Event15th IEEE International Conference on Robotics and Automation, ICRA 1998 - Leuven, Belgium
Duration: May 16 1998May 20 1998

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2
ISSN (Print)1050-4729

Other

Other15th IEEE International Conference on Robotics and Automation, ICRA 1998
CountryBelgium
CityLeuven
Period5/16/985/20/98

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Weighting observations: The use of kinematic models in object tracking'. Together they form a unique fingerprint.

Cite this