Learning the Incremental Warp for 3D Vehicle Tracking in LiDAR Point Clouds

Learning the Incremental Warp for 3D Vehicle Tracking in LiDAR Point Clouds

Object tracking from LiDAR point clouds, which are always incomplete, sparse, and unstructured, plays a crucial role in urban navigation. Some existing methods utilize a learned similarity network for locating the target, immensely limiting the advancements in tracking accuracy. In this study, we le...

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Bibliographic Details
Main Authors: Shengjing Tian, Xiuping Liu, Meng Liu, Yuhao Bian, Junbin Gao, Baocai Yin
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
point clouds
3D tracking
state estimation
Siamese network
deep LK
Online Access:https://www.mdpi.com/2072-4292/13/14/2770

Internet

https://www.mdpi.com/2072-4292/13/14/2770

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