Dual-biomimetic curved compound-eye camera system for multi-target distance measurement in a large field of view
Year: 2024
Type: article
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.
Source: Optics Express
DOI: 10.1364/oe.535365
Authors: Yiming Liu, Huangrong Xu, Yuanjie Zhang, Dengshan Wu, Xiaojun Zhou, Qingyang Meng, Yuanyuan Wang, Weixing Yu
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,270
Awards: G2733489338, G3839381779, G7292156234
OpenAlex ID: W4403646480
