A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVGIP: Image Understanding
Contour Matching Using Epipolar Geometry
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Acquiring a Radiance Distribution to Superimpose Virtual Objects onto a Real Scene
IEEE Transactions on Visualization and Computer Graphics
Structure and Motion from Line Segments in Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Creating Image-Based VR Using a Self-Calibrating Fisheye Lens
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Automatic line matching across views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Omnidirectional camera model and epipolar geometry estimation by RANSAC with bucketing
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Estimation of omnidirectional camera model from epipolar geometry
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Camera Models and Fundamental Concepts Used in Geometric Computer Vision
Foundations and Trends® in Computer Graphics and Vision
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This paper presents a novel approach to both omnidirectional camera calibration and 3D reconstruction of the surrounding scene by contour matching in architectural scenes. By using a quantitative measure to consider the inlier distribution, we can estimate more precise camera model parameters and structure from motion. Since most of line segments of man-made objects are projected to the contours in omnidirectional images, contour matching problem is important in camera recovery process. We propose a novel 3D reconstruction method by contour matching in three omnidirectional views. First, two points on the contour and their viewing vectors are used to determine an interpretation plane equation, and we obtain a contour intersecting both the plane and the estimated patch of the camera model. Then, 3D line segment is calculated from two patches, which is projected to the contour on the third views, and these matching results are used in refinement of camera recovery.