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Article

BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data

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Virtual Reality and Multimedia Group, Institute of Computer Science, Freiberg University of Mining and Technology, 09599 Freiberg, Germany
2
Operating Systems and Communication Technologies Group, Institute of Computer Science, Freiberg University of Mining and Technology, 09599 Freiberg, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Sylvie Le Hegarat-Mascle
Sensors 2021, 21(6), 2144; https://doi.org/10.3390/s21062144
Received: 29 January 2021 / Revised: 4 March 2021 / Accepted: 10 March 2021 / Published: 18 March 2021
(This article belongs to the Section Remote Sensors)
Common Machine-Learning (ML) approaches for scene classification require a large amount of training data. However, for classification of depth sensor data, in contrast to image data, relatively few databases are publicly available and manual generation of semantically labeled 3D point clouds is an even more time-consuming task. To simplify the training data generation process for a wide range of domains, we have developed the BLAINDER add-on package for the open-source 3D modeling software Blender, which enables a largely automated generation of semantically annotated point-cloud data in virtual 3D environments. In this paper, we focus on classical depth-sensing techniques Light Detection and Ranging (LiDAR) and Sound Navigation and Ranging (Sonar). Within the BLAINDER add-on, different depth sensors can be loaded from presets, customized sensors can be implemented and different environmental conditions (e.g., influence of rain, dust) can be simulated. The semantically labeled data can be exported to various 2D and 3D formats and are thus optimized for different ML applications and visualizations. In addition, semantically labeled images can be exported using the rendering functionalities of Blender. View Full-Text
Keywords: machine learning; depth-sensing; LiDAR; Sonar; virtual sensors; labeling; Blender machine learning; depth-sensing; LiDAR; Sonar; virtual sensors; labeling; Blender
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MDPI and ACS Style

Reitmann, S.; Neumann, L.; Jung, B. BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data. Sensors 2021, 21, 2144. https://doi.org/10.3390/s21062144

AMA Style

Reitmann S, Neumann L, Jung B. BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data. Sensors. 2021; 21(6):2144. https://doi.org/10.3390/s21062144

Chicago/Turabian Style

Reitmann, Stefan, Lorenzo Neumann, and Bernhard Jung. 2021. "BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data" Sensors 21, no. 6: 2144. https://doi.org/10.3390/s21062144

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