NDLI: Automatic Line Extraction in Uncalibrated Omnidirectional Cameras with Revolution Symmetry

Content Provider	Springer Nature Link
Author	Bermudez Cameo, J. Lopez Nicolas, G. Guerrero, J. J.
Copyright Year	2014
Abstract	Revolution symmetry is a realistic assumption for modelling the majority of catadioptric and dioptric cameras. In central systems it can be described by a projection model based on radially symmetric distortion. In these systems straight lines are projected on curves called line-images. These curves have in general more than two degrees of freedom and their shape strongly depends on the particular camera configuration. Therefore, the existing line-extraction methods for this kind of omnidirectional cameras require the camera calibration by contrast with the perspective case where the calibration is not involved in the shape of the projected line-image. However, this drawback can be considered as an advantage because the shape of the line-images can be used for self-calibration. In this paper, we present a novel method to extract line-images in uncalibrated omnidirectional images which is valid for radially symmetric central systems. In this method we propose using the plumb-line constraint to find closed form solutions for different types of camera systems, dioptric or catadioptric. The inputs of the proposed method are points belonging to the line-images and their intensity gradient. The gradient information allows to reduce the number of points needed in the minimal solution improving the result and the robustness of the estimation. The scheme is used in a line-image extraction algorithm to obtain lines from uncalibrated omnidirectional images without any assumption about the scene. The algorithm is evaluated with synthetic and real images showing good performance. The results of this work have been implemented in an open source Matlab toolbox for evaluation and research purposes.
Starting Page	16
Ending Page	37
Page Count	22
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	114
Issue Number	1
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2015-01-07
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Omnidirectional vision Line features Uncalibrated images Fisheye Catadioptric Single-image Matlab toolbox Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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