Mr. Yaming Wang Profile

Yaming Wang

at Tianjin Jinhang Institute of Technical Physics

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Proceedings Article | 27 March 2022 Paper

Object detection for large-scale outdoor point cloud based on deep learning

Yaming Wang, Xiaodong Jia, Kui Zhou

Proceedings Volume 12169, 1216906 (2022) https://doi.org/10.1117/12.2619490

KEYWORDS: Target detection, Neural networks, Remote sensing, LIDAR, Target detection, Neural networks, Remote sensing, LIDAR

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A object detection method based on RandLA-Net efficient semantic segmentation network is designed based on the analysis of a variety of current neural networks for real-time obstacle detection during low-altitude flight of helicopters. The method first uses RandLA-Net for semantic segmentation of point clouds, and in order to improve the recognition ability of the network for tall obstacles, the local feature aggregation module in the network is improved accordingly, then the target class of interest is clustered and segmented, and the clustering results are obtained by improving the traditional Euclidean clustering method, and finally the 3D boundingbox of the target is obtained based on the principle of principal component analysis. The paper focuses on the algorithm's ability to identify obstacles such as power lines and tall towers. After actually collecting data and constructing data sets for validation, the final results show that the method can detect targets more accurately, laying a theoretical foundation for application to real-time detection systems.

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