1. 青海省基础测绘院
2. 青海省自然资源遥感中心
纸质出版:2023
移动端阅览
宋秀容, 全雪贞, 张洁, 等. 结合局部与全局特征的点云语义分割卷积网络[J]. 地理空间信息, 2023,21(3):25-30.
宋秀容, 全雪贞, 张洁, et al. 结合局部与全局特征的点云语义分割卷积网络[J]. 2023, 21(3): 25-30.
点云语义分割在许多与点云相关的应用程序中具有重要作用,特别是对于机载激光点云,精确的注释可大大扩展其在各种应用中的用途。然而,受限于传感器噪声、复杂的对象结构、不完整的点和不均匀的点密度,准确而有效的语义分割仍是一项艰巨的任务。因此,提出了一种结合局部与全局特征的机载激光点云语义分割网络。首先利用改进的渐进三角化不规则网络致密化滤波算法将点云划分为地面点和非地面点,然后针对非地面点分别提取局部和全局特征,再聚合局部特征和全局特征并获得点标记结果,最后基于图优化模型进行语义标签优化。为评估该方法性能,在一个大规模机载激光点云数据集中进行测试实验。结果表明,该方法在DALES基准数据集上的总体精度可提高至97.4%,对8个语义类进行分类,mIoU为78.2%。与其他较前沿方法相比,该方法可实现更高的分割精度。
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