@inproceedings{9e50cb682b854e64abd81c086f571a10,
title = "3D small-scale object recognition network in cluttered point cloud scenes",
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.",
keywords = "Adaptive instantiation, Cluttered point cloud, Normal-angle feature, Sampling strategy, Semantic segmentation, Small-scale object",
author = "Zhengmao Sun and Junhua Sun and Jie Zhang",
note = "Publisher Copyright: Copyright {\textcopyright} 2021 SPIE.; 2021 Applied Optics and Photonics China: Infrared Device and Infrared Technology, AOPC 2021 ; Conference date: 20-06-2021 Through 22-06-2021",
year = "2021",
doi = "10.1117/12.2605034",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "HaiMei Gong and Zelin Shi and Jin Lu",
booktitle = "AOPC 2021",
address = "美国",
}