计算机应用 ›› 2014, Vol. 34 ›› Issue (2): 585-588.

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于骨架特征的人数统计

夏菁菁,高琳,范勇,段晶晶,任新宇,刘旭,高攀   

  1. 西南科技大学 计算机科学与技术学院, 四川 绵阳 621010
  • 收稿日期:2013-07-10 修回日期:2013-09-11 出版日期:2014-02-01 发布日期:2014-03-01
  • 通讯作者: 夏菁菁
  • 作者简介:夏菁菁(1987-),女,四川广安人,硕士研究生,主要研究方向:计算机视觉;高琳(1976-),男,湖北襄樊人,讲师,博士,主要研究方向:计算机视觉、数字图像处理;范勇(1972-),男,重庆人,教授,博士,主要研究方向:机器视觉、图像理解;段晶晶(1988-),女,河南驻马店人,硕士研究生,主要研究方向:图形图像处理;任新宇(1988-),男,四川泸州人,硕士研究生,主要研究方向:计算机视觉;刘旭(1988-),女,四川安岳人,硕士研究生,主要研究方向:计算机视觉;高攀(1988-),男,四川眉山人,硕士,主要研究方向:计算机视觉。
  • 基金资助:
    四川省教育厅科技项目;西南科技大学研究生创新基金资助项目;四川省科技创新苗子工程资助项目

People counting based on skeleton feature

XIA Jingjing,GAO Lin,FAN Yong,DUAN Jingjing,REN Xinyu,LIU Xu,GAO Pan   

  1. College of Computer Science and Technology, Southwest University of Science and Technology, Mianyang Sichuan 621010, China
  • Received:2013-07-10 Revised:2013-09-11 Online:2014-02-01 Published:2014-03-01
  • Contact: XIA Jingjing

摘要: 针对视频监控中行人在运动中将出现部分或严重遮挡的问题,提出了一种基于人体骨架特征的人数统计算法。首先,利用形态学骨架提取算法提取初始人体骨架图;然后,剔除骨架孤立点和骨架伪分支,得到最优人体骨架特征;最后,通过分析骨架的人头区域特征,建立人头检测响应规则,检测行人人头个数实现人数统计。实验结果表明,该算法能够解决视频监控人物相互之间部分遮挡和严重遮挡问题,针对相对稀疏的场景该算法人数统计准确率为95%左右。

关键词: 人数统计, 人头检测, 骨架特征, 前景检测, 检测响应规则

Abstract: Concerning the problem that pedestrians would be partially or seriously shaded by each other in video monitoring, this paper proposed a people counting algorithm based on human body skeleton feature. At first, the initial human skeleton was extracted by morphological skeleton extraction algorithm. Then the optimal skeleton feature was obtained by eliminating outliers and pseudo branches. Finally, this paper established a head detection response rule through analyzing the characteristics of skeleton in head areas to detect the head of pedestrian, and completed people counting by counting the heads of pedestrians. The experimental results show that the algorithm can solve the problems of partial and serious shading in video monitoring. For relatively sparse scene, the overall people counting accuracy rate of the algorithm is about 95%.

Key words: people counting, head detection, skeleton feature, foreground detection, detection response rule

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