{"title":"Calibration Method for Ultra-Wide FOV Fisheye Cameras Based on Improved Camera Model and SE(3) Image Pre-Correction","authors":"Rui Xing, Fenghua He, Yu Yao","doi":"10.1049/ipr2.70021","DOIUrl":null,"url":null,"abstract":"<p>The severe radial distortion of ultra-wide field of view (FOV) fisheye camera results in poor model fitting and challenges in calibration board detection. In this paper, a novel calibration method for ultra-wide FOV fisheye cameras is proposed based on improved camera model and SE(3) image pre-correction. Initially, a method to extend the maximum fitting FOV of the camera model to over 180 degrees is proposed. Subsequently, a calibration board detection approach is proposed using SE(3) image pre-correction. Specifically, image pre-correction is incorporated into the camera calibration process, utilizing SE(3) to define the pre-correction plane. Calibration boards are detected within the pre-corrected images, enhancing the reliability, accuracy and speed of board detection in distorted images, consequently increasing the control point's maximum FOV. Lastly, the improved camera model and SE(3) image pre-correction are integrated into a feedback-based camera calibration system for ultra-wide FOV fisheye cameras. Operating with real-time or offline video streams as input, this system autonomously selects calibration key frames, optimizes camera parameters and calibration board poses in real-time. Simulation and real-world experiments verify the effectiveness of the proposed method, leading to a 62% increase in the achievable maximum FOV.</p>","PeriodicalId":56303,"journal":{"name":"IET Image Processing","volume":"19 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ipr2.70021","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Image Processing","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ipr2.70021","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The severe radial distortion of ultra-wide field of view (FOV) fisheye camera results in poor model fitting and challenges in calibration board detection. In this paper, a novel calibration method for ultra-wide FOV fisheye cameras is proposed based on improved camera model and SE(3) image pre-correction. Initially, a method to extend the maximum fitting FOV of the camera model to over 180 degrees is proposed. Subsequently, a calibration board detection approach is proposed using SE(3) image pre-correction. Specifically, image pre-correction is incorporated into the camera calibration process, utilizing SE(3) to define the pre-correction plane. Calibration boards are detected within the pre-corrected images, enhancing the reliability, accuracy and speed of board detection in distorted images, consequently increasing the control point's maximum FOV. Lastly, the improved camera model and SE(3) image pre-correction are integrated into a feedback-based camera calibration system for ultra-wide FOV fisheye cameras. Operating with real-time or offline video streams as input, this system autonomously selects calibration key frames, optimizes camera parameters and calibration board poses in real-time. Simulation and real-world experiments verify the effectiveness of the proposed method, leading to a 62% increase in the achievable maximum FOV.
期刊介绍:
The IET Image Processing journal encompasses research areas related to the generation, processing and communication of visual information. The focus of the journal is the coverage of the latest research results in image and video processing, including image generation and display, enhancement and restoration, segmentation, colour and texture analysis, coding and communication, implementations and architectures as well as innovative applications.
Principal topics include:
Generation and Display - Imaging sensors and acquisition systems, illumination, sampling and scanning, quantization, colour reproduction, image rendering, display and printing systems, evaluation of image quality.
Processing and Analysis - Image enhancement, restoration, segmentation, registration, multispectral, colour and texture processing, multiresolution processing and wavelets, morphological operations, stereoscopic and 3-D processing, motion detection and estimation, video and image sequence processing.
Implementations and Architectures - Image and video processing hardware and software, design and construction, architectures and software, neural, adaptive, and fuzzy processing.
Coding and Transmission - Image and video compression and coding, compression standards, noise modelling, visual information networks, streamed video.
Retrieval and Multimedia - Storage of images and video, database design, image retrieval, video annotation and editing, mixed media incorporating visual information, multimedia systems and applications, image and video watermarking, steganography.
Applications - Innovative application of image and video processing technologies to any field, including life sciences, earth sciences, astronomy, document processing and security.
Current Special Issue Call for Papers:
Evolutionary Computation for Image Processing - https://digital-library.theiet.org/files/IET_IPR_CFP_EC.pdf
AI-Powered 3D Vision - https://digital-library.theiet.org/files/IET_IPR_CFP_AIPV.pdf
Multidisciplinary advancement of Imaging Technologies: From Medical Diagnostics and Genomics to Cognitive Machine Vision, and Artificial Intelligence - https://digital-library.theiet.org/files/IET_IPR_CFP_IST.pdf
Deep Learning for 3D Reconstruction - https://digital-library.theiet.org/files/IET_IPR_CFP_DLR.pdf