Quantitative planar region detection
International Journal of Computer Vision
Robust detection of degenerate configurations while estimating the fundamental matrix
Computer Vision and Image Understanding
Autocalibration from Planar Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Driving into the Future with ITS
IEEE Intelligent Systems
Multiple planes based registration using 3D Projective Space for Augmented Reality
Image and Vision Computing
Parametric estimation of affine deformations of planar shapes
Pattern Recognition
Automatic change detection of driving environments in a vision-based driver assistance system
IEEE Transactions on Neural Networks
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For detecting multiple planar regions rapidly in the image sequence, this paper proposed a novel algorithm. First of all, the method uses RANSAC to detect a dominant homography, then, it calculates the poles corresponding to the two images based on homography constraint and classifies all the matching feature points into two sets. When we detect the homography corresponding to more planes based on RANSAC once more, only three pairs of feature points should be selected from the classified feature points, that is define the to-be-determined plane homography model together with a pair of poles, and this can improve the detection efficiency. Simulation and real experiment results show that the proposed algorithm is robust to the existence of mismatched features and is applicable to either stereo or motion sequence images.