3D Model-based 6D Object Pose Tracking on RGB Images using Particle Filtering and Heuristic Optimization

Mateusz Majcher, Bogdan Kwolek

2020

Abstract

We present algorithm for tracking 6D pose of the object in a sequence of RGB images. The images are acquired by a calibrated camera. The object of interest is segmented by an U-Net neural network. The network is trained in advance to segment a set of objects from the background. The 6D pose of the object is estimated through projecting the 3D model to image and then matching the rendered object with the segmented object. The objective function is calculated using object silhouette and edge scores determined on the basis of distance transform. A particle filter is used to estimate the posterior probability distribution. A k-means++ algorithm, which applies a sequentially random selection strategy according to a squared distance from the closest center already selected is executed on particles representing multi-modal probability distribution. A particle swarm optimization is then used to find the modes in the probability distribution. Results achieved by the proposed algorithm were compared with results obtained by a particle filter and a particle swarm optimization.

Paper Citation

in Harvard Style

Majcher M. and Kwolek B. (2020). 3D Model-based 6D Object Pose Tracking on RGB Images using Particle Filtering and Heuristic Optimization. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 690-697. DOI: 10.5220/0009365706900697

in Bibtex Style

@conference{visapp20,
author={Mateusz Majcher and Bogdan Kwolek},
title={3D Model-based 6D Object Pose Tracking on RGB Images using Particle Filtering and Heuristic Optimization},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={690-697},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009365706900697},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - 3D Model-based 6D Object Pose Tracking on RGB Images using Particle Filtering and Heuristic Optimization
SN - 978-989-758-402-2
AU - Majcher M.
AU - Kwolek B.
PY - 2020
SP - 690
EP - 697
DO - 10.5220/0009365706900697
PB - SciTePress