Laser & Infrared, Volume. 54, Issue 12, 1948(2024)
Point cloud registration method based on 3DHarris-FPFH features
[6] [6] Shi Xiaojing, Liu Tao, Han Xie. Improved Iterative Closest Point (ICP) 3D point cloud registration algorithm based on point cloud filtering and adaptive fireworks for coarse registration[J]. International Journal of Remote Sensing, 2020, 41(8): 3197-3220.
[7] [7] Zhang Juyong, Yao Yuxin, Deng Bailin. Fast and robust iterative closest point.[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(7): 3450-3466.
[9] [9] Zhang Wannan. Robust registration of SAR and optical images based on deep learning and improved Harris algorithm[J]. Scientific Reports, 2022, 12(1): 5901-5901.
[10] [10] Li Peng, Wang Jian, Zhao Yindi, et al. Improved algorithm for point cloud registration based on fast point feature histograms[J]. Journal of Applied Remote Sensing, 2016, 10(4): 045024.
[11] [11] Liu Jinda, Hou Yanyang, Pei Hongxing. An improved random sample consensus based on density-based spatial clustering of applications with noise for image mosaic[J]. Pattern Recognition and Image Analysis, 2021, 31(4): 625-631.
Get Citation
Copy Citation Text
JING Hui-cheng, WANG Rui-yu, ZHANG Jing-xuan, WANG Yi, BAO Qi-long, YANG Fu-quan. Point cloud registration method based on 3DHarris-FPFH features[J]. Laser & Infrared, 2024, 54(12): 1948
Category:
Received: Mar. 25, 2024
Accepted: Apr. 3, 2025
Published Online: Apr. 3, 2025
The Author Email: ZHANG Jing-xuan (jingxuan.zhang@ncst.edu.cn)