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Cross-source point cloud registration: Challenges, progress and prospects
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DOI：10.1016/j.neucom.2023.126383.png)
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Abstract
En 中文
The emerging topic of cross-source point cloud (CSPC) registration has attracted increasing attention with the fast development background of 3D sensor technologies. Different from the conventional same -source point clouds that focus on data from same kind of 3D sensor (e.g., Kinect), CSPCs come from dif-ferent kinds of 3D sensors (e.g., Kinect and LiDAR). CSPC registration generalizes the requirement of data acquisition from same-source to different sources, which leads to generalized applications and combines the advantages of multiple sensors. In this paper, we provide a systematic review on CSPC registration. We first present the characteristics of CSPC, and then summarize the key challenges in this research area, followed by the corresponding research progress consisting of the most recent and representative devel-opments on this topic. Finally, we discuss the important research directions in this vibrant area and explain the role in several application fields.& COPY; 2023 Elsevier B.V. All rights reserved.
Keywords:
Point cloud registration
Survey
Deep learning
Optimization
Cross -source dataset
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