Coupled 3D tracking and pose optimization of rigid objects using particle filter

Abstract

CONTRIBUTION In order to track and estimate the pose of rigid objects with high accuracy in unconstrained environment, we propose a framework that combines 3D particle filter with algebraic pose optimization in a closed loop. The contributions include: 1. A new Particle Filter observation model based on line similarity in 3D space; 2. Coupled tracking and algebraic pose optimization in Particle Filter framework; 3. A dynamic ROI is developed which reduces the line detection and search space for real-time application.

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Cite this paper

@inproceedings{Yang2012Coupled3T, title={Coupled 3D tracking and pose optimization of rigid objects using particle filter}, author={Heng Yang and Yueqiang Zhang and Xiaolin Liu and Ioannis Patras}, booktitle={ICPR}, year={2012} }