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Authors: Marlon Marcon 1 ; Olga Bellon 2 and Luciano Silva 2

Affiliations: 1 Dapartment of Software Engineering, Federal University of Technology - Paraná, Dois Vizinhos, Brazil ; 2 Department of Computer Science, Federal University of Paraná, Curitiba, Brazil

Keyword(s): Transfer Learning, 3D Computer Vision, Feature-based Registration, ICP Dense Registration, RGB-D Images.

Abstract: Object recognition and 6DoF pose estimation are quite challenging tasks in computer vision applications. Despite efficiency in such tasks, standard methods deliver far from real-time processing rates. This paper presents a novel pipeline to estimate a fine 6DoF pose of objects, applied to realistic scenarios in real-time. We split our proposal into three main parts. Firstly, a Color feature classification leverages the use of pre-trained CNN color features trained on the ImageNet for object detection. A Feature-based registration module conducts a coarse pose estimation, and finally, a Fine-adjustment step performs an ICP-based dense registration. Our proposal achieves, in the best case, an accuracy performance of almost 83% on the RGB-D Scenes dataset. Regarding processing time, the object detection task is done at a frame processing rate up to 90 FPS, and the pose estimation at almost 14 FPS in a full execution strategy. We discuss that due to the proposal’s modularity, we could le t the full execution occurs only when necessary and perform a scheduled execution that unlocks real-time processing, even for multitask situations. (More)

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Paper citation in several formats:
Marcon, M.; Bellon, O. and Silva, L. (2021). Towards Real-time Object Recognition and Pose Estimation in Point Clouds. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-488-6; ISSN 2184-4321, pages 164-174. DOI: 10.5220/0010265601640174

@conference{visapp21,
author={Marlon Marcon. and Olga Bellon. and Luciano Silva.},
title={Towards Real-time Object Recognition and Pose Estimation in Point Clouds},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2021},
pages={164-174},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010265601640174},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Towards Real-time Object Recognition and Pose Estimation in Point Clouds
SN - 978-989-758-488-6
IS - 2184-4321
AU - Marcon, M.
AU - Bellon, O.
AU - Silva, L.
PY - 2021
SP - 164
EP - 174
DO - 10.5220/0010265601640174

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