计算机与现代化

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基于改进HOG特征值的行人检测

  

  1. 陕西省行政学院,陕西宝鸡710068
  • 收稿日期:2014-11-17 出版日期:2015-02-28 发布日期:2015-03-06
  • 作者简介:张桂宁(1984),女,陕西宝鸡人,陕西省行政学院助理工程师,本科,研究方向:视觉系统与行人检测,计算机网络与信息安全。
  • 基金资助:
    陕西省自然科学基金资助项目(2010F47); 陕西省行政学院科研立项(YKT010)

Study on Pedestrian Detection Based on Improved HOG Eigenvalues

  1. Department of Electronic Equipment and Information Management, Shaanxi Academy
    of Governance, Baoji 710068, China
  • Received:2014-11-17 Online:2015-02-28 Published:2015-03-06

摘要:
摘要:针对目前梯度方向直方图HOG作为描述符应用于行人检测时,会自动忽略梯度方向相反方向的差异,导致HOG的表达能力较弱等不足,本文提出基于改进HOG特征值的行人检测机制。在分析HOG描述符基础上,串联直方图,设计改进的HOG描述符;并提出一种新的归一化技术,嵌入改进的HOG描述符中,增强其表达能力。在多个数据库上的实验结果表明:与传统HOG特征方法相比,本文方法具有更高的准确率和更低的漏检率。

关键词: HOG特征, 行人检测, 梯度方向, 直方图归一化, 漏检率

Abstract: The pedestrian detection mechanism was proposed for solving these defects such as weak expression ability of HOG reduced by automatically ignoring differences in the opposite direction of its gradient direction when taking the current gradient direction histogram as descriptor for applying to pedestrian detection. Basing on analysis of the traditional HOG descriptor, the improved HOG descriptor was designed by connecting histograms; and a new normalization technique was proposed to embed into the improved HOG descriptor for enhancing its expression ability. The experiments results basing on several datasets show that: comparison with traditional HOG feature method, this proposed mechanism had higher accuracy and lower miss rate.

Key words:  , improved HOG feature; pedestrian detection; gradient direction; histogram normalization; lower miss rate

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