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用于大视野多目标距离测量的双仿生弯曲复眼相机系统

Dual-biomimetic curved compound-eye camera system for multi-target distance measurement in a large field of view.

作者信息

Liu Yiming, Xu Huangrong, Zhang Yuanjie, Wu Dengshan, Zhou Xiaojun, Meng Qingyang, Wang Yuanyuan, Yu Weixing

出版信息

Opt Express. 2024 Nov 4;32(23):41870-41881. doi: 10.1364/OE.535365.

DOI:10.1364/OE.535365
PMID:39573485
Abstract

Biomimetic curved compound-eye cameras (BCCECs) have attracted great attention for their potential applications in a variety of fields such as target recognition, monitor and three-dimensional localization in military due to their unique optical properties such as large field of view (FOV) and small size. In this work, we proposed a multi-target distance measurement method based on a dual-BCCEC system in a large FOV. To guarantee the precise measurement of the distance of multiple targets, a feature point searching and matching algorithm is developed for the dual-BCCEC system to improve the localizing efficiency of common feature points. In addition, a CALibration Tag (CALTag) self-recognition calibration method is also developed to calibrate ommatidia of the BCCEC with a high efficiency. Based on these two methods, the coordinates of multiple targets with clear feature points can be obtained after the distortion correction in sub-images and thus the distances of multiple targets with clear feature points can be achieved simultaneously with a single compound-eye raw image. The experiment results show that the dual-BCCEC system has a high distant measurement accuracy with an error of less than 6.80% for at least ten different targets in the a working distance ranging from 400 to 600 m in a quite large FOV of 98°×98°. The method demonstrated in this work can pave the way for multi-targets tracking in those related areas with high security monitoring requirements.

摘要

仿生曲面复眼相机(BCCECs)因其独特的光学特性,如大视场(FOV)和小尺寸,在目标识别、军事监测和三维定位等多个领域的潜在应用中备受关注。在这项工作中,我们提出了一种基于双BCCEC系统的大视场多目标距离测量方法。为了保证对多个目标距离的精确测量,针对双BCCEC系统开发了一种特征点搜索与匹配算法,以提高公共特征点的定位效率。此外,还开发了一种校准标签(CALTag)自识别校准方法,以高效校准BCCEC的小眼。基于这两种方法,在对子图像进行畸变校正后,可以获得具有清晰特征点的多个目标的坐标,从而利用单幅复眼原始图像同时实现具有清晰特征点的多个目标的距离测量。实验结果表明,在98°×98°的相当大视场中,双BCCEC系统在400至600 m的工作距离范围内,对至少十个不同目标的远距离测量精度较高,误差小于6.80%。本文所展示的方法可为那些具有高安全监测要求的相关领域中的多目标跟踪铺平道路。

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