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Authors: Rafal Staszak and Dominik Belter

Affiliation: Institute of Control, Robotics and Information Engineering, Poznan University of Technology, Poznan and Poland

Keyword(s): Object Pose Estimation, Convolutional Neural Networks, Deep Learning in Robotics.

Related Ontology Subjects/Areas/Topics: Environmental Monitoring and Control ; Hybrid Learning Systems ; Image Processing ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control ; Vision, Recognition and Reconstruction

Abstract: In this research, we focus on the 6D pose estimation of known objects from the RGB image. In contrast to state of the art methods, which are based on the end-to-end neural network training, we proposed a hybrid approach. We use separate deep neural networks to: detect the object on the image, estimate the center of the object, and estimate the translation and ”in-place” rotation of the object. Then, we use geometrical relations on the image and the camera model to recover the full 6D object pose. As a result, we avoid the direct estimation of the object orientation defined in SO3 using a neural network. We propose the 4D-NET neural network to estimate translation and ”in-place” rotation of the object. Finally, we show results on the images generated from the Pascal VOC and ShapeNet datasets.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Staszak, R. and Belter, D. (2019). Hybrid 6D Object Pose Estimation from the RGB Image. In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-380-3; ISSN 2184-2809, SciTePress, pages 541-549. DOI: 10.5220/0007933105410549

@conference{icinco19,
author={Rafal Staszak. and Dominik Belter.},
title={Hybrid 6D Object Pose Estimation from the RGB Image},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2019},
pages={541-549},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007933105410549},
isbn={978-989-758-380-3},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Hybrid 6D Object Pose Estimation from the RGB Image
SN - 978-989-758-380-3
IS - 2184-2809
AU - Staszak, R.
AU - Belter, D.
PY - 2019
SP - 541
EP - 549
DO - 10.5220/0007933105410549
PB - SciTePress