系统仿真学报 ›› 2026, Vol. 38 ›› Issue (1): 14-28.doi: 10.16182/j.issn1004731x.joss.25-0214

• 论文 • 上一篇    下一篇

基于改进RBOT的增强现实三维跟踪注册方法

周家锐1, 崔海华1, 李鹏程1, 顾施濠1, 郝惠朴1, 赵西富1, 赵安安1, 姜涛2   

  1. 1.南京航空航天大学 机电学院,江苏 南京 210016
    2.宿迁学院 机电学院,江苏 宿迁 223800
  • 收稿日期:2025-03-20 修回日期:2025-04-24 出版日期:2026-01-18 发布日期:2026-01-28
  • 通讯作者: 崔海华
  • 第一作者简介:周家锐(2001-),男,硕士生,研究方向为增强现实、计算机视觉。
  • 基金资助:
    国家自然科学基金青年科学基金(52305582);2024江苏省青年科技人才托举工程(JSTJ-2024-663);中国航空发动机集团产学研合作项目(HFZL2022CXY006);航空基金(2022Z072052002)

3D Object Tracking Registration Based on Improved RBOT Method

Zhou Jiarui1, Cui Haihua1, Li Pengcheng1, Gu Shihao1, Hao Huipu1, Zhao Xifu1, Zhao Anan1, Jiang Tao2   

  1. 1.College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
    2.College of Mechanical and Electrical Engineering, Suqian University, Suqian 223800, China
  • Received:2025-03-20 Revised:2025-04-24 Online:2026-01-18 Published:2026-01-28
  • Contact: Cui Haihua

摘要:

针对基于区域的目标跟踪(region-based object racking,RBOT)方法在各向同性物体和背景颜色相似情况下的不足,提出一种融合边缘特征的改进方法。利用边缘检测算法提取目标轮廓,设计区域分割策略,将其融入能量函数框架,以优化前景内部的线与边缘特征,提高动态环境适应性和位姿估计精度。通过航空发动机增强现实装配应用验证试验,结果表明:所提方法可有效降低旋转和平移误差,初始化位姿偏差<1.5°,位移偏差<0.5%;静态视频流相邻帧间姿态抖动<0.3°,位移抖动<0.1%,满足虚实注册装配引导的精度需求。

关键词: 增强现实, 位姿估计, 边缘检测, 图像处理, 航空发动机

Abstract:

To address the limitations of region-based object tracking (RBOT) in handling isotropic objects and scenarios with similar foreground-background colors, an improved method integrating edge features is proposed. The approach employs edge detection to extract object contours and designs a region segmentation strategy incorporated into an energy function framework to optimize internal line and edge consistency, thereby enhancing adaptability in dynamic environments and improving pose estimation accuracy. Validation through augmented reality assembly experiments on an aero-engine demonstrates that the proposed method effectively reduces rotational and translational errors, achieving initialization deviations of less than 1.5° and 0.5%, respectively. For static video sequences, inter-frame pose jitter remains below 0.3° and displacement jitter below 0.1%, meeting the precision requirements of virtual-real registration for assembly guidance.

Key words: augmented reality, position estimation, edge detection, image processing, aero-engines

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