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Real-Time Texturing for 6D Object Instance Detection from RGB Images

Rojtberg, Pavel and Kuijper, Arjan (2019):
Real-Time Texturing for 6D Object Instance Detection from RGB Images.
pp. 295-300, 2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), Beijing, China, 10.-18. Oct., ISBN 978-1-7281-4765-9,
DOI: 10.1109/ISMAR-Adjunct.2019.00-25,
[Conference or Workshop Item]

Abstract

For objected detection, the availability of color cues strongly influences detection rates and is even a prerequisite for many methods. However, when training on synthetic CAD data, this information is not available. We therefore present a method for generating a texture-map from image sequences in real-time. The method relies on 6 degree-of-freedom poses and a 3D-model being available. In contrast to previous works this allows interleaving detection and texturing for upgrading the detector on-the-fly. Our evaluation shows that the acquired texture-map significantly improves detection rates using the LINEMOD [5] detector on RGB images only. Additionally, we use the texture-map to differentiate instances of the same object by surface color.

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Rojtberg, Pavel and Kuijper, Arjan
Title: Real-Time Texturing for 6D Object Instance Detection from RGB Images
Language: English
Abstract:

For objected detection, the availability of color cues strongly influences detection rates and is even a prerequisite for many methods. However, when training on synthetic CAD data, this information is not available. We therefore present a method for generating a texture-map from image sequences in real-time. The method relies on 6 degree-of-freedom poses and a 3D-model being available. In contrast to previous works this allows interleaving detection and texturing for upgrading the detector on-the-fly. Our evaluation shows that the acquired texture-map significantly improves detection rates using the LINEMOD [5] detector on RGB images only. Additionally, we use the texture-map to differentiate instances of the same object by surface color.

ISBN: 978-1-7281-4765-9
Uncontrolled Keywords: Artificial intelligence (AI) Modeling of physical attributes Recovery of physical attributes Pattern recognition Implementations Interactive systems
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)
Event Location: Beijing, China
Event Dates: 10.-18. Oct.
Date Deposited: 09 Apr 2020 10:48
DOI: 10.1109/ISMAR-Adjunct.2019.00-25
Official URL: https://doi.org/10.1109/ISMAR-Adjunct.2019.00-25
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