We present a new framework for correcting multiperspective distortions using collineations. A collineation describes the transformation between the images of a camera due to changes in sampling and image plane selection. We show that image distortions in many previous models of cameras can be effectively reduced via proper collineations. To correct distortions in a specific multiperspective camera, we develop an interactive system that allows users to select feature rays from the camera and position them at the desirable pixels. Our system then computes the optimal collineation to match the projections of these rays with the corresponding pixels. Experiments demonstrate that our system robustly corrects complex distortions without acquiring the scene geometry, and the resulting images appear nearly undistorted.
Multiperspective Distortion Correction Using Collineations
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
2007-01-01
11 pages
Article/Chapter (Book)
Electronic Resource
English
Scale Invariant Feature Transform , Image Distortion , Projective Transformation , Pinhole Camera , Distortion Correction Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence , Biometrics , Algorithm Analysis and Problem Complexity
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