Abstract
Planar surfaces are important characteristics in man-made environments and have been successfully applied to camera calibration and interactive modeling. We develop a method for detecting planes in image pairs under epipolar constraints using planar homographies. In order to extract the whole planes, the normalized cut method is used to segment the original images. We pick those segmented regions that best fit a triangulation of the homography inliers as the detected planes. We illustrate the algorithm’s performance using gray-level and color image pairs.KeywordsAugmented RealityPlanar SurfaceImage PairDelaunay TriangulationCamera CalibrationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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