Feature Point Correspondence in the Presence of Occlusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Bayesian Model Estimation and Selection for Epipolar Geometry and Generic Manifold Fitting
International Journal of Computer Vision
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Problem of poor camera calibration in Augmented Reality (AR) has always been overcome by employing careful camera calibration steps with the use of specific known object. However, this task is time consuming and mostly performed offline. A Self-Calibrated AR system (SCAR system) of a camera updates the camera intrinsic parameters whenever they change. The system solves the camera parameters based on only three views and requires only the fundamental matrices as the inputs. Point correspondence matching is one of the necessary stages in SCAR system. Correct corner matches ensure good estimation of the fundamental matrix since the outcome of this stage is to be fed into the fundamental matrix estimation stage. This paper proposes a simple and robust algorithm for point correspondence matching in one of the stages of SCAR system. The matching process is efficient and capable of removing outliers from corner detection as well as maintaining a good number of correct matches even in the event of occlusion.