中国科学院软件研究所机构知识库
Advanced  
ISCAS OpenIR  > 人机交互技术与智能信息处理实验室  > 期刊论文
Title:
self-calibration of hybrid central catadioptric and perspective cameras
Author: Deng Xiaoming ; Wu Fuchao ; Wu Yihong ; Duan Fuqing ; Chang Liang ; Wang Hongan
Source: Computer Vision and Image Understanding
Issued Date: 2012
Volume: 116, Issue:6, Pages:715-729
Indexed Type: EI
Department: (1) Institute of Software, Chinese Academy of Sciences, P.O. Box 8718, Beijing 100190, China; (2) National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, China; (3) College of Information Science and Technology, Beijing Normal University, No. 19, XinJieKouWai Street, Beijing 100875, China; (4) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, P.O. Box 8718, Beijing 100190, China
English Abstract: Hybrid central catadioptric and perspective cameras are desired in practice, because the hybrid camera system can capture large field of view as well as high-resolution images. However, the calibration of the system is challenging due to heavy distortions in catadioptric cameras. In addition, previous calibration methods are only suitable for the camera system consisting of perspective cameras and catadioptric cameras with only parabolic mirrors, in which priors about the intrinsic parameters of perspective cameras are required. In this work, we provide a new approach to handle the problems. We show that if the hybrid camera system consists of at least two central catadioptric and one perspective cameras, both the intrinsic and extrinsic parameters of the system can be calibrated linearly without priors about intrinsic parameters of the perspective cameras, and the supported central catadioptric cameras of our method can be more generic. In this work, an approximated polynomial model is derived and used for rectification of catadioptric image. Firstly, with the epipolar geometry between the perspective and rectified catadioptric images, the distortion parameters of the polynomial model can be estimated linearly. Then a new method is proposed to estimate the intrinsic parameters of a central catadioptric camera with the parameters in the polynomial model, and hence the catadioptric cameras can be calibrated. Finally, a linear self-calibration method for the hybrid system is given with the calibrated catadioptric cameras. The main advantage of our method is that it cannot only calibrate both the intrinsic and extrinsic parameters of the hybrid camera system, but also simplify a traditional nonlinear self-calibration of perspective cameras to a linear process. Experiments show that our proposed method is robust and reliable. © 2012 Elsevier Inc. All rights reserved.
Language: 英语
WOS ID: WOS:000303430200005
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14718
Appears in Collections:人机交互技术与智能信息处理实验室_期刊论文

Files in This Item:
File Name/ File Size Content Type Version Access License
1-s2.0-S1077314212000355-main.pdf(920KB)----限制开放 联系获取全文

Recommended Citation:
Deng Xiaoming,Wu Fuchao,Wu Yihong,et al. self-calibration of hybrid central catadioptric and perspective cameras[J]. Computer Vision and Image Understanding,2012-01-01,116(6):715-729.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Deng Xiaoming]'s Articles
[Wu Fuchao]'s Articles
[Wu Yihong]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Deng Xiaoming]‘s Articles
[Wu Fuchao]‘s Articles
[Wu Yihong]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2020  中国科学院软件研究所 - Feedback
Powered by CSpace