3D small-scale object recognition network in cluttered point cloud scenes

Zhengmao Sun; Junhua Sun; Jie Zhang

doi:10.1117/12.2605034

24 November 2021 3D small-scale object recognition network in cluttered point cloud scenes

Zhengmao Sun, Junhua Sun, Jie Zhang

Proceedings Volume 12061, AOPC 2021: Infrared Device and Infrared Technology; 120610R (2021) https://doi.org/10.1117/12.2605034
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

This paper proposes a recognition network for small-scale objects in cluttered point clouds. The network consists of two components: improved semantic segmentation for large-scale 3D point clouds and an adaptive instantiation algorithm. In semantic segmentation, based on the backbone, we introduce the grid sampling module and the normal-angle feature to improve the efficiency and accuracy of segmentation respectively. Then the network outputs point-wise semantic labels. After that, we propose an adaptive instantiation algorithm to group points that are closely packed together and obtain the objects. In this way, our network completes the recognition of the small-scale objects. We conducted experiments on real aero-engine datasets and the results reveal that the proposed network can recognize a small-sized component in the cluttered point cloud scene of aero-engine.

Citation Download Citation

Zhengmao Sun, Junhua Sun, and Jie Zhang "3D small-scale object recognition network in cluttered point cloud scenes", Proc. SPIE 12061, AOPC 2021: Infrared Device and Infrared Technology, 120610R (24 November 2021); https://doi.org/10.1117/12.2605034

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