摘要
机器视觉应用场景复杂化和功能需求多元化给三维成像技术带来巨大挑战。针对复杂环境及受限空间的目标重建和场景感知问题,结构简单且性能可靠的单相机三维视觉成像技术能够提供重要的解决途径。在阐明单相机三维立体视觉成像理论模型的基础上,根据相机运动情况以及采用的反射、折射或衍射等附加光学元件的情况,分类介绍了单相机三维视觉成像系统组成、基本原理和实现方法。从视场范围、空间分辨率、视角灵活性、动态响应性、环境适应性等角度,分析了现有单相机三维视觉成像方法的优越性和局限性。围绕三维重建精度及成像质量提升问题,回顾了相机与附加光学元件未对准参数的主要标定方法。结合单相机三维视觉成像的技术挑战和应用前景,展望了其在实现大视场高分辨率、高动态高实时性、复杂环境适应性等方面的发展方向。
Three-dimensional(3D) imaging faces challenges due to machine vision requiring complicated applications and diverse functionalities. Due to its compact structure and reliable performance, 3D imaging using single-camera stereo vision(SSV) offers a considerable approach to object reconstruction and situational awareness under spatially-limited conditions. In this paper, we demonstrated the theoretical basis for SSV-based 3D imaging. Next, we introduced 3D imaging techniques based on known or unknown camera motion, and those using reflective, refractive, or diffractive optical elements based on system setup, basic principle, and implementation methods. Furthermore, we analyzed existing methods based on their strengths and shortcomings in the field of view, spatial resolution, viewpoint flexibility, and dynamic response. Particularly, the calibration methods of misalignment parameters between the camera and optical element are reviewed to enhance 3D reconstruction accuracy. In addition to the technical challenges and potential applications, we discussed the development trends of SSV-based 3D imaging toward a wide field of view, high resolution,high dynamic and real-time capability, and strong environmental adaptability.
作者
刘兴盛
李安虎
邓兆军
陈昊
Liu Xingsheng;Li Anhu;Deng Zhaojun;Chen Hao(School of Mechanical Engineering,Tongji University,Shanghai 201804,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2022年第14期77-95,共19页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61975152)。
关键词
机器视觉
三维成像
立体视觉
相机运动
光学元件
参数标定
machine vision
three-dimensional imaging
stereo vision
camera motion
optical element
parameter calibration