基于双目点云的三维物体检测准确性分析 |
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作者姓名: | 刘王超 娄鑫 |
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作者单位: | 1. 上海科技大学信息科学与技术学院, 上海 201210;2. 中国科学院上海微系统与信息技术研究所, 上海 200050;3. 中国科学院大学电子电气与通信工程学院, 北京 100049 |
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基金项目: | 国家自然科学基金(61801292)和上海青年科技英才扬帆计划(18YF1416600)资助 |
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摘 要: | 双目相机虽然能通过算法生成密集的深度数据,但其在精度上与激光雷达生成的深度数据有着较大的差距,特别是在纹理不明显的区域。针对这种现象,尝试使用激光雷达的精确点云来排除由双目相机产生的pseudo-LiDAR数据中与之差别较大的部分点,然后将优化后的pseudo-LiDAR用以进行三维物体检测。实验结果显示,将pseudo-LiDAR数据中的不准确点(坏点)排除,有助于提高检测准确率,最多可提高21.02%。因此,如何不依赖激光雷达数据来排除pseudo-LiDAR点云中的坏点是进一步提高双目相机系统检测准确率的关键。
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关 键 词: | 三维物体检测 激光雷达 双目相机 点云 误差 |
收稿时间: | 2020-05-18 |
修稿时间: | 2020-08-28 |
Accuracy analysis of 3D object detection based on stereo point cloud |
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Authors: | LIU Wangchao LOU Xin |
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Institution: | 1. School of Information Science & Technology, ShanghaiTech University, Shanghai 201220, China;2. Shanghai Institute of Microsystem & Information Technology, Chinese Academy of Sciences, Shanghai 200050, China;3. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Science, Beijing 100049, China |
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Abstract: | 3D object detection is a crucial task in autonomous driving. Recently, the accuracy of LiDAR-based 3D object detection algorithms have improved dramatically. However, if we replace the LiDAR data with the depth map that generates from stereo cameras, the detection performance drops a lot. In a recent research, it is found that by transforming the stereo-based depth map to point cloud representation, referred to as pseudo-LiDAR, the performance of 3D object detection can be improved significantly. However, there is still a big gap of accuracy between LiDAR-based and stereo-based algorithms. One of the main reasons is that there are error points in the transformed pseudo-LiDAR data. To study this, we use the LiDAR points cloud to correct the pseudo-LiDAR data, i.e., to detect and exclude the error points. Then we use the optimized pseudo-LiDAR to perform 3D object detection. Experimental results show that the detection accuracy can be improved by as much as 21.02%. |
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Keywords: | 3D object detection LiDAR stereo cameras point cloud error |
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