Real-Time 3D Object Detection from Point Cloud through Foreground Segmentation

doi:10.1109/ACCESS.2021.3087179

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	Real-Time 3D Object Detection from Point Cloud through Foreground Segmentation
	B. Wang; M. Zhu; Y. Lu; J. Wang; W. Gao and H. Wei
刊名	IEEE Access
	2021
卷号	9 页码:84886-84898
ISSN号	21693536
DOI	10.1109/ACCESS.2021.3087179
英文摘要	This paper aims to apply real-time light-weight high-precision 3D detection for autonomous driving. We propose LIDAR-based 3D object detection based on foreground segmentation using a fully sparse convolutional network (FS23D). We design a sparse convolutional backbone network and a sparse convolutional detection head to efficiently use the computing and memory resources and accelerate the inference. Instead of using the anchor-based method, we convert the detection problem into a foreground segmentation problem on a bird's-eye view. The sparse convolutional detection head predicts the objectness and bounding box on each active point on the sparse feature map. We design a new oriented bounding box coding method and corresponding loss functions. We predict the endpoints of two mutually perpendicular lines that pass through the foreground active points and indirectly predict the objects' oriented bounding box from these four endpoints. We use the indirectly calculated object center, size, and orientation as inputs of loss functions in the training step. Experiments on the KITTI dataset show that the sparse backbone network we designed is 2.2 times faster and 18.4 times fewer FLOPs than the dense backbone network. The average improvement of the loss functions based on the bounding box code is 1.1% and 0.8% on the BEV and 3D detection, respectively, compared to no addition of these losses. Moreover, FS23D outperforms the state-of-the-art LIDAR-based method in speed and precision for both cars and cyclists. 2013 IEEE.
URL标识	查看原文
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/65575]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	B. Wang,M. Zhu,Y. Lu,et al. Real-Time 3D Object Detection from Point Cloud through Foreground Segmentation[J]. IEEE Access,2021,9:84886-84898.
APA	B. Wang,M. Zhu,Y. Lu,J. Wang,&W. Gao and H. Wei.(2021).Real-Time 3D Object Detection from Point Cloud through Foreground Segmentation.IEEE Access,9,84886-84898.
MLA	B. Wang,et al."Real-Time 3D Object Detection from Point Cloud through Foreground Segmentation".IEEE Access 9(2021):84886-84898.