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Obstacle recognition in front of vehicle based on geometry information and corrected laser intensity

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Abstract

Accurate identification and classification of obstacles in front of vehicle is an important part of intelligent vehicle safety driving. To solve the difficulties in distinguishing geometry similar obstacles and blocked obstacles, a real-time algorithm to accurately identify vehicles and pedestrians in a single frame was presented using laser intensity correction model and obstacle characteristic information. To complete the identification of obstacles, there are two classifications; the first classification according to the diagonal lengths of obstacles’ minimum enclosing rectangle, and then the second classification according to the mean and variance of intensity. As for different overlap criterion, result shows that the classification performance of our methods is better than other methods available.

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Authors and Affiliations

  1. Shandong University of Technology, Zibo, China

    Jiangliang Huang, Derong Tan, Liang Sun, Jinju Shao, Yaojuan Ma & Zhangu Wang

Authors
  1. Jiangliang Huang
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  2. Derong Tan
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  3. Liang Sun
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  4. Jinju Shao
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  5. Yaojuan Ma
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  6. Zhangu Wang
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Correspondence to Jiangliang Huang.

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Huang, J., Tan, D., Sun, L. et al. Obstacle recognition in front of vehicle based on geometry information and corrected laser intensity. Artif Life Robotics 23, 338–344 (2018). https://doi.org/10.1007/s10015-018-0446-x

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  • DOI: https://doi.org/10.1007/s10015-018-0446-x

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