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A new pedestrian detection method based on combined HOG and LSS features

机译:一种结合HOG和LSS特征的行人检测新方法

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摘要

Pedestrian detection is a critical issue in computer vision, with several feature descriptors can be adopted. Since the ability of various kinds of feature descriptor is different in pedestrian detection and there is no basis in feature selection, we analyze the commonly used features in theory and compare them in experiments. It is desired to find a new feature with the strongest description ability from their pair-wise combinations. In experiments, INRIA database and Daimler database are adopted as the training and testing set. By theoretic analysis, we find the HOG-LSS combined feature have more comprehensive description ability. At first, Adaboost is regarded as classifier and the experimental results show that the description ability of the new combination features is improved on the basis of the single feature and HOG-LSS combined feature has the strongest description ability. For further verifying this conclusion, SVM classifier is used in the experiment. The detection performance is evaluated by miss rate, the false positives per window, and the false positives per image. The results of these indicators further prove that description ability of HOG-LSS feature is better than other combination of these features. (C) 2014 Elsevier B.V. All rights reserved.
机译:行人检测是计算机视觉中的关键问题,可以采用多个特征描述符。由于行人检测中各种特征描述符的能力不同,并且特征选择没有依据,因此我们在理论上分析了常用特征,并在实验中进行了比较。期望从它们的成对组合中找到具有最强描述能力的新特征。在实验中,采用INRIA数据库和戴姆勒数据库作为训练和测试集。通过理论分析,发现HOG-LSS组合特征具有更全面的描述能力。首先,将Adaboost视为分类器,实验结果表明,新组合特征的描述能力在单一特征的基础上得到了提高,HOG-LSS组合特征的描述能力最强。为了进一步验证该结论,在实验中使用了SVM分类器。通过未命中率,每个窗口的误报和每个图像的误报来评估检测性能。这些指标的结果进一步证明了HOG-LSS特征的描述能力优于这些特征的其他组合。 (C)2014 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2015年第3期|1006-1014|共9页
  • 作者单位

    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China;

    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China;

    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China;

    Anhui Univ, Coll Elect Engn & Automat, Hefei 230039, Anhui, Peoples R China;

    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China;

    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, 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

    Pedestrian detection; Feature combination; SVM; Adaboost;

    机译:行人检测;特征组合;支持向量机;Adaboost;

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