摘要
人体检测是家庭服务机器人的一项基本功能.本文针对复杂家庭环境,倒地人体面临地上杂物的干扰、遮挡等情况下,提出一种结合三维点云分割和局部特征匹配的倒地人体检测方法.该方法对点云进行分割之后将每个物体横向切分成若干段,对每段点云采用局部特征匹配并分类,并根据匹配段数来判断是否为倒地人体.实验结果表明,该方法在0.3秒的检测时间内,实现平均误识别率低于10%的高检测率,满足服务机器人实时性要求的同时具有良好的鲁棒性,即使人体部分被遮挡,依然可以检测到各种倒地姿态的人.
Human detection is a basic functionality for home service robots. For complex family environments where lying person is partially occluded or in cluster, this paper proposes a lying person detection approach integrates 3D point cloud segmentation and local feature matching. Our approach segments the point cloud of each object into several pieces, matches local features of each object piece, and classifies them to detect lying person. Experiments show that our approach can achieve high detection accuracy with average recognition time less than 0.3s. Our approach meets the human detection requirements for service robots and is demonstrated to be practical and reliable, even when parts of human body is occluded.
出处
《计算机系统应用》
2016年第10期186-191,共6页
Computer Systems & Applications
基金
国家自然科学基金(61175057)
关键词
家庭服务机器人
三维点云分割
倒地人体检测
特征匹配
home service robot
lying person detection
3D point cloud segmentation
feature matching
