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International Conference on Cognitive Systems and Signal Processing

ICCSIP 2022: Cognitive Systems and Information Processing pp 617–631Cite as

A 3D Point Cloud Object Detection Algorithm Based on MSCS-Pointpillars

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1787))

Abstract

As an important technique of driverless vehicles, 3D Point Cloud Object Detection algorithm can provide semantic information and geometrical information of various types of objects. For the problem of feature information loss in 3D Point Cloud Object Detection, this paper proposes an improved Pointpillars algorithm where a multi-scale columnar feature extraction network based on the attention mechanism. In this algorithm we extract features to obtain pseudo-images of different scales, and splicing point cloud pseudo-images of multiple scales to obtain fusion feature maps. In addition, by introducing a Convolutional Block Attention Module (CBAM), our MSCS-Piontpillars can effectively suppress the noise in the pseudo-image of the point cloud and amplify the important feature information for target classification. Comparision experimental was carried on both the KITTI 3D Object dataset and a real experiment. The results show that compared with Pointpillars, MSCS-Pointpillars (Multi-Scale Channel Spatial Attention Pointpillars) have improved the detection accuracy of cars, cyclists, pedestrians and other targets.

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Authors and Affiliations

  1. School of Automobile, Chang’an University, Xi’an, 710064, Shanxi, China

    Zengfeng Song, Yang Gao & Honggang Luan

Authors
  1. Zengfeng Song
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  2. Yang Gao
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  3. Honggang Luan
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Corresponding author

Correspondence to Zengfeng Song .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Fuchun Sun

  2. University of Manchester, Manchester, UK

    Angelo Cangelosi

  3. Universität Hamburg, Hamburg, Germany

    Jianwei Zhang

  4. Fuzhou University, Fuzhou, China

    Yuanlong Yu

  5. Tsinghua University, Beijing, China

    Huaping Liu

  6. Tsinghua University, Beijing, China

    Bin Fang

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Song, Z., Gao, Y., Luan, H. (2023). A 3D Point Cloud Object Detection Algorithm Based on MSCS-Pointpillars. In: Sun, F., Cangelosi, A., Zhang, J., Yu, Y., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2022. Communications in Computer and Information Science, vol 1787. Springer, Singapore. https://doi.org/10.1007/978-981-99-0617-8_45

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  • DOI: https://doi.org/10.1007/978-981-99-0617-8_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0616-1

  • Online ISBN: 978-981-99-0617-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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