摘要
深度测量是立体视觉研究的重要问题,本文提出一种基于全向图与结构光的深度测量方法.首先,根据测量系统特点,采用了基于多参考面的投影仪标定算法;然后,设计了一组"四方位沙漏状"编码结构光,实现待测图像与参考图像的对应点计算;最后,在移动条件下,研究基于先验约束迭代就近点(Iterative closest point,ICP)的深度点云匹配算法.实验结果表明,本文方法可以准确地对室内场景进行深度测量,且抗干扰能力较强.
Depth measurement is an important problem in stereovision. A depth measurement method based on omnidirectional image and structured light is proposed. Firstly, according to the measurement system characteristics, main research attentions are paid to the study of projector calibration algorithm based on multiple reference planes. Secondly,a group of "four direction sand clock-like" encoding structured light is designed. It can be used to compute the corresponding points between the measured image and reference image. Thirdly, under a mobile condition, a depth point-cloud matching algorithm based on prior-constraint iterative closest point(ICP) is studied. Experimental results demonstrate that the proposed method can acquire omnidirectional depth information of large-scale scenes accurately, and has high anti-interference abilility.
出处
《自动化学报》
EI
CSCD
北大核心
2015年第9期1553-1562,共10页
Acta Automatica Sinica
基金
国家自然科学基金(61273078)
教育部博士点基金(20110042120030)
中央高校基础科研业务费(130404012)资助~~
关键词
深度测量
全向图
结构光
立体视觉
Depth measurement
omnidirectional image
structured light
stereovision