顾宏

206

  • 教授     博士生导师   硕士生导师
  • 性别:男
  • 毕业院校:浙江大学
  • 学位:博士
  • 所在单位:控制科学与工程学院
  • 学科:模式识别与智能系统
  • 办公地点:创新园大厦B0715
  • 电子邮箱:guhong@dlut.edu.cn

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开通时间:2025.3.31

最后更新时间:2025.3.31

Automatic Generation of Synthetic LiDAR Point Clouds for 3-D Data Analysis

点击次数:98

论文类型:期刊论文

发表时间:2019-07-01

发表刊物:IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

收录刊物:SCIE、EI

卷号:68

期号:7

页面范围:2671-2673

ISSN号:0018-9456

关键字:Deep learning; semantic segmentation; synthetic light detection and ranging (LiDAR) point clouds

摘要:The recent success of deep learning in 3-D data analysis relies upon the availability of large annotated data sets. However, creating 3-D data sets with point-level labels are extremely challenging and require a huge amount of human efforts. This paper presents a novel open-sourced method to extract light detection and ranging point clouds with ground truth annotations from a simulator automatically. The virtual sensor can be configured to simulate various real devices, from 2-D laser scanners to 3-D real-time sensors. Experiments are conducted to show that using additional synthetic data for training can: 1) achieve a visible performance boost in accuracy; 2) reduce the amount of manually labeled real-world data; and 3) help to improve the generalization performance across data sets.