Elements of information theory
Elements of information theory
A Theory of Single-Viewpoint Catadioptric Image Formation
International Journal of Computer Vision
The Trace Transform and Its Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Optimization for Geometric Computation: Theory and Practice
Statistical Optimization for Geometric Computation: Theory and Practice
Digital Image Processing
Catadioptric Projective Geometry
International Journal of Computer Vision
A Unifying Theory for Central Panoramic Systems and Practical Applications
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Image Processing in Catadioptric Planes: Spatiotemporal Derivatives and Optical Flow Computation
OMNIVIS '02 Proceedings of the Third Workshop on Omnidirectional Vision
Catadioptric Line Features Detection using Hough Transform
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Detection of Image Structures Using the Fisher Information and the Rao Metric
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Fisher-Rao Metric for Projective Transformations of the Line
International Journal of Computer Vision
Digital Image Processing: PIKS Scientific Inside
Digital Image Processing: PIKS Scientific Inside
Application of the Fisher-Rao Metric to Ellipse Detection
International Journal of Computer Vision
The randomized-Hough-transform-based method for great-circle detection on sphere
Pattern Recognition Letters
Fast Central Catadioptric Line Extraction
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Fitting conics to paracatadioptric projections of lines
Computer Vision and Image Understanding
RANSAC based ellipse detection with application to catadioptric camera calibration
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Line Localization from Single Catadioptric Images
International Journal of Computer Vision
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In a central paracatadioptric imaging system a perspective camera takes an image of a scene reflected in a paraboloidal mirror. A 360° field of view is obtained, but the image is severely distorted. In particular, straight lines in the scene project to circles in the image. These distortions make it difficult to detect projected lines using standard image processing algorithms.The distortions are removed using a Fisher-Rao metric which is defined on the space of projected lines in the paracatadioptric image. The space of projected lines is divided into subsets such that on each subset the Fisher-Rao metric is closely approximated by the Euclidean metric. Each subset is sampled at the vertices of a square grid and values are assigned to the sampled points using an adaptation of the trace transform. The result is a set of digital images to which standard image processing algorithms can be applied. The effectiveness of this approach to line detection is illustrated using two algorithms, both of which are based on the Sobel edge operator. The task of line detection is reduced to the task of finding isolated peaks in a Sobel image. An experimental comparison is made between these two algorithms and third algorithm taken from the literature and based on the Hough transform.