A theory of self-calibration of a moving camera
International Journal of Computer Vision
Geometric computation for machine vision
Geometric computation for machine vision
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Geometric Camera Calibration Using Circular Control Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Calibration from Rigid Motions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Epipolar Geometry Estimation of Binocular Stereo Heads
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo geometry from 3D ego-motion streams
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Determining relative geometry of cameras from normal flows
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
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The increasing use of active vision systems makes it necessary to determine the relative geometry between the cameras in the system at arbitrary time. There has been some work on on-line estimation of the relative camera geometry parameters. However, many of them are based on epipolar geometry, motion correspondences, or even presence of some calibration reference objects in the scene. In this paper, we describe a method that allows the relative geometry of two cameras be estimated without assuming that their visual fields picture the same object, nor that motion correspondences in each camera are fully estimated beforehand. The method starts from monocular normal flows in the two cameras and estimates the relative geometry parameters without evening accessing the full optical flows. Experimental results are shown to illustrate the performance of the method.