吉林大学学报(信息科学版) ›› 2015, Vol. 33 ›› Issue (2): 214-218.

• 论文 • 上一篇    下一篇

基于RGB-D 数据的实时人体检测算法

郑立国, 刘杨, 罗江林, 李宏研   

  1. 吉林世纪元时空动漫游戏科技股份有限公司动画工程研究中心, 长春130012
  • 收稿日期:2014-11-25 出版日期:2015-03-24 发布日期:2015-05-29
  • 作者简介:郑立国(1964—), 男, 吉林华甸人, 吉林世纪元时空动漫游戏科技股份有限公司研究员, 主要从事企业管理研究, (Tel)86-13601213186(E-mail)jldhxy0613@ sina. com; 通讯作者: 刘杨(1982—), 女, 长春人, 吉林世纪元时空动漫游戏科技股份有限公司工程师, 主要从事计算机视觉算法研究, (Tel)86-13944118040(E-mail)lyang1983@163. com。
  • 基金资助:

    2013 年吉林省高技术产业发展专项基金资助项目(2013G006); 2013 年国家科技支撑计划基金资助项目(2013BAH24F00)

Implementation of Real-Time Human Body Detection Based on RGB-D Data

ZHENG Liguo, LIU Yang, LUO Jianglin, LI Hongyan   

  1. Animation Engineering Research Center, Jilin Fifth Dimension Animation & Games Technology Company Limited, Changchun 130012, China
  • Received:2014-11-25 Online:2015-03-24 Published:2015-05-29

摘要:

为实现体感控制器中的人体骨架识别功能, 提出了基于RGB鄄D 数据的实时人体检测算法, 并在人体检测中予以实现。首先对原始3D 点云数据进行简化, 对地平面进行移除, 然后对剩余的点云数据进行初步分类,得到人体点云数据簇, 对初步分类后的人体点云数据簇进行二次精细分类, 进而实现了地面上的多个人体的检测。该方法不仅能检测出静止的多个人体, 而且能检测行走中的多个人体。实验结果表明, 该方法实时性好, CPU 实时处理速率可达到25 帧/ s, 而且无论对于静止的人体还是行走中的人体, 该方法的人体检测准确度都能达到86%以上。

关键词: 实时人体检测, K 邻域, 点云简化, 方向梯度直方图

Abstract:

In order to achieve skeleton identification function of body feeling controller, engineers must implement human body detection. We present a real-time detection method based on rgb-d data and the effect of its implementation on body detection. First, simplify the original 3D point cloud. Second, remove the ground plane. Third, for the rest of the point cloud data, the preliminary classification is performed to get human point cloud data cluster. Again after the first classification do the secondary fine classification, and then implement multiple human body detection. This method can detect multiple human body in static, and also can detect multiple human body in walking. Experimental results show that this method has good real-time performance,and CPU real-time processing speed can reach 25 frames per second. No matter to the static human body or the walking human body, the method is more accurate and rapid in detection, and the human body detection accuracy can reach 86%.

Key words: real-time people detection, K-nearest neighbors, simplification of point cloud, histogram of oriented depths(HOD)

中图分类号: 

  • TP391. 4