Title: Relational object tracking and learning
Authors: Nitti, Davide
De Laet, Tinne
De Raedt, Luc
Issue Date: Jun-2014
Host Document: 2014 IEEE International Conference on Robotics and Automation pages:935 -942
Conference: IEEE International Conference on Robotics and Automation (ICRA) date:June 2014
Abstract: We propose a relational model for online object
tracking during human activities using the Distributional
Clauses Particle Filter framework, which allows to encode
commonsense world knowledge such as qualitative physical
laws, object properties as well as relations between them. We tested the framework during a packaging activity where many objects are invisible for longer periods of time. In addition, we extended the framework to learn the parameters online and tested it in a tracking scenario involving objects connected by strings.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Informatics Section
Tutorial services, Faculty of Engineering

Files in This Item:
File Description Status SizeFormat
ICRA14_0737_FI.pdf Published 1547KbAdobe PDFView/Open


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science