计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 145-150.doi: 10.11896/jsjkx.190900172
沈琦1, 陈逸伦2, 刘枢3, 刘利刚1
SHEN Qi1, CHEN Yi-lun2, LIU Shu3, LIU Li-gang1
摘要： 文中提出了一种基于激光雷达点云的三维目标检测算法VoxelRCNN(Voxelization Region-Based Convolutional Neural Networks),该算法基于VoxelNet三维目标检测网络算法,将RCNN算法的思想从二维目标检测运用到三维目标检测中。VoxelRCNN算法由两级构成,第一级的目标是用区域提案网络提取候选区域框信息,第二级的目标是对第一级提取的目标检测框进行更精细的修正,以得到更精确的目标检测结果。第一级网络对整个场景的点云进行体素化,对每个体素块提取特征作为卷积神经网络的输入,经过卷积神经网络计算得到最后的特征图,根据特征图对包围盒信息进行回归学习。第二级网络依据第一级提取的候选区域信息以及特征信息,通过池化得到等大特征信息,再次回归学习包围盒信息。在KITTI数据集上的实验结果表明,提出的网络结构是有意义的。
中图分类号:
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