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RBNet: A Deep Neural Network for Unified Road and Road Boundary Detection

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10634))

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Abstract

Accurately detecting road and its boundary on the images is an essential task for vision-based autonomous driving systems. However, prevailing methods either only detect road or add an extra processing stage to detect road boundary. In this work, we introduce a deep neural network, called Road and road Boundary detection Network (RBNet), that can detect both road and road boundary in a single process. In specific, we first investigate the contextual relationship between the road structure and its boundary arrangement and then model them with a Bayesian network. By implementing the Bayesian model, the RBNet can learn to simultaneously estimate the probabilities of a pixel on the image belonging to the road and road boundary. Comprehensive evaluations are carried out based on the well-known road benchmark, which can demonstrate the compelling performance of the proposed method.

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Notes

  1. 1.

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

  2. 2.

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

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Author information

Authors and Affiliations

  1. School of Information Technology, UBTECH Sydney Artificial Intelligence Centre, The University of Sydney, Darlington, NSW, 2006, Australia

    Zhe Chen

  2. Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology Sydney, Ultimo, NSW, 2007, Australia

    Zijing Chen

Authors
  1. Zhe Chen
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  2. Zijing Chen
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Corresponding author

Correspondence to Zhe Chen .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Chen, Z., Chen, Z. (2017). RBNet: A Deep Neural Network for Unified Road and Road Boundary Detection. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10634. Springer, Cham. https://doi.org/10.1007/978-3-319-70087-8_70

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  • DOI: https://doi.org/10.1007/978-3-319-70087-8_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70086-1

  • Online ISBN: 978-3-319-70087-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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