Quantitative Measure of Inlier Distributions and Contour Matching for Omnidirectional Camera Calibration

This paper presents a novel approach to both the calibration of the omnidirectional camera and the contour matching in architectural scenes. The proposed algorithm divides an entire image into several sub-regions, and then examines the number of the inliers in each sub-region and the area of each region. In our method, the standard deviations are used as quantitative measure to select a proper inlier set. Since the line segments of man-made objects are projected to contours in omnidirectional images, contour matching problem is important for more precise camera recovery. We propose a novel contour matching method using geometrical information of the omnidirectional camera.

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