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Vehicle detection based on visual attention mechanism and adaboost cascade classifier in intelligent transportation systems

机译:基于视觉注意机制和智能交通系统的Adaboost级联分类器的车辆检测

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摘要

Robust and efficient vehicle detection is an essential task in intelligent transportation systems (ITS). Unfortunately, due to a great diversity of vehicle profiles and outdoor illumination conditions, it is a challenge to detect vehicles effectively. This paper proposes a method for high-performance vehicle detection based on visual attention mechanism and AdaBoost cascade classifier. Our method constructs the structural Haar features and extracts the features of samples using structural Haar features and trains an AdaBoost cascade classifier. Then we use the visual attention mechanism to extract the target candidate region. At last, we generate detecting sub-windows in the candidate region and discriminate them with the cascade classifier to realize vehicle detection. We compare the performance of this method against two variants, one using MB-LBP features and another using Haar features. The experimental results demonstrate satisfactory performance for the proposed method in term of training speed, detecting speed and detecting accuracy.
机译:鲁棒和高效的车辆检测是智能交通系统(其)中的必备任务。遗憾的是,由于车辆概况和户外照明条件巨大,因此有效地检测车辆是一项挑战。本文提出了一种基于视觉注意机制和Adaboost级联分类器的高性能车辆检测方法。我们的方法构造了结构哈尔特征,并使用结构哈尔特征提取样品的特征,并列进Adaboost级联分类器。然后我们使用视觉注意机制来提取目标候选区域。最后,我们在候选区域中生成检测子窗口,并用级联分类器区分它们以实现车辆检测。我们将这种方法的性能与两个变体进行比较,一个使用MB-LBP功能,另一个使用Haar功能。实验结果表明,在训练速度,检测速度和检测精度的术语中表现出令人满意的方法。

著录项

  • 来源
    《Optical and quantum electronics》 |2019年第8期|263.1-263.18|共18页
  • 作者单位

    Nanjing Univ Sci & Technol Sch Elect & Opt Engn Dept Optoelect Technol Nanjing 210094 Jiangsu Peoples R China;

    Nanjing Univ Sci & Technol Sch Elect & Opt Engn Dept Optoelect Technol Nanjing 210094 Jiangsu Peoples R China;

    Nanjing Univ Sci & Technol Sch Elect & Opt Engn Dept Optoelect Technol Nanjing 210094 Jiangsu Peoples R China;

    Nanjing Univ Sci & Technol Sch Elect & Opt Engn Dept Optoelect Technol Nanjing 210094 Jiangsu Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Visual attention mechanism; Vehicle detection; Structural Haar features; AdaBoost;

    机译:视觉注意机制;车辆检测;结构哈尔特征;Adaboost;

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