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International Symposium on Visual Computing

ISVC 2020: Advances in Visual Computing pp 422–435Cite as

BVNet: A 3D End-to-End Model Based on Point Cloud

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12509))

Abstract

Point cloud LiDAR data are increasingly used for detecting road situations for autonomous driving. The most important issues here are the detection accuracy and the processing time. In this study, we propose a new model which can improve the detection performance based on point cloud. A well-known difficulty in processing 3D point cloud is that the point data are unordered. To address this problem, we define 3D point cloud features in the grid cells of the bird’s view according to the distribution of the points. In particular, we introduce the average and standard deviation of the heights as well as a distance-related density of the points as new features inside a cell. The resulting feature map is fed into a conventional neural network to obtain the outcomes, thus realizing an end-to-end real-time detection framework, called BVNet (Bird’s-View-Net). The proposed model is tested on the KITTI benchmark suit and the results show considerable improvement for the detection accuracy compared with the models without the newly introduced features.

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Notes

  1. 1.

    http://www.cvlibs.net/datasets/kitti/eval_3dobject.php.

  2. 2.

    Huawei atlas support: https://support.huawei.com/enterprise/en.

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Author information

Authors and Affiliations

  1. Process Optimization Group, Technische Universität Ilmenau, 98693, Ilmenau, Germany

    Nuo Cheng & Pu Li

  2. LiangDao GmbH, 12099, Berlin, Germany

    Nuo Cheng, Xiaohan Li & Shengguang Lei

Authors
  1. Nuo Cheng
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  2. Xiaohan Li
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  3. Shengguang Lei
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  4. Pu Li
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Corresponding author

Correspondence to Nuo Cheng .

Editor information

Editors and Affiliations

  1. University of Nevada Reno, Reno, NV, USA

    George Bebis

  2. Stony Brook University, Stony Brook, NY, USA

    Zhaozheng Yin

  3. Drexel University, Philadelphia, PA, USA

    Edward Kim

  4. RWTH Aachen University, Aachen, Germany

    Jan Bender

  5. University of Edinburgh, Edinburgh, UK

    Kartic Subr

  6. IBM Research – Cambridge, Cambridge, MA, USA

    Bum Chul Kwon

  7. University of Waterloo, Waterloo, ON, Canada

    Jian Zhao

  8. Graz University of Technology, Graz, Austria

    Denis Kalkofen

  9. The Hong Kong Polytechnic University, Hong Kong, Hong Kong

    George Baciu

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Cheng, N., Li, X., Lei, S., Li, P. (2020). BVNet: A 3D End-to-End Model Based on Point Cloud. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science(), vol 12509. Springer, Cham. https://doi.org/10.1007/978-3-030-64556-4_33

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  • DOI: https://doi.org/10.1007/978-3-030-64556-4_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64555-7

  • Online ISBN: 978-3-030-64556-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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