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RGB-D Road Segmentation Based on Geometric Prior Information

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Pattern Recognition and Computer Vision (PRCV 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14425))

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Abstract

Deep data can provide rich spatial structure information, which can effectively exclude the interference of lighting and road texture in road segmentation. This paper proposes a road segmentation model based on two kinds of a priori knowledge: disparity information, and surface normal vector information. Then, a two-branch neural network is used to process the color image and the processed depth image separately, and an effective fusion module is designed to make full use of the complementary features of the two modalities. The experimental results on the KITTI road detection dataset and Cityscape dataset show that the method in this paper has good road segmentation performance.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, China

    Xinyi Wu, Xia Yuan, YanChao Cui & ChunXia Zhao

Authors
  1. Xinyi Wu
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  2. Xia Yuan
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  3. YanChao Cui
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  4. ChunXia Zhao
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Corresponding author

Correspondence to Xia Yuan .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Qingshan Liu

  2. Xiamen University, Xiamen, China

    Hanzi Wang

  3. Beijing University of Posts and Telecommunications, Beijing, China

    Zhanyu Ma

  4. Sun Yat-sen University, Guangzhou, China

    Weishi Zheng

  5. Peking University, Beijing, China

    Hongbin Zha

  6. Chinese Academy of Sciences, Beijing, China

    Xilin Chen

  7. Chinese Academy of Sciences, Beijing, China

    Liang Wang

  8. Xiamen University, Xiamen, China

    Rongrong Ji

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wu, X., Yuan, X., Cui, Y., Zhao, C. (2024). RGB-D Road Segmentation Based on Geometric Prior Information. In: Liu, Q., et al. Pattern Recognition and Computer Vision. PRCV 2023. Lecture Notes in Computer Science, vol 14425. Springer, Singapore. https://doi.org/10.1007/978-981-99-8429-9_35

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  • DOI: https://doi.org/10.1007/978-981-99-8429-9_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8428-2

  • Online ISBN: 978-981-99-8429-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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