Abstract
An vanishing point is defined as the convergence point of lines in an image plane that is produced by the projection of parallel lines in real space. Vanishing points can provide strong cues for inferring information about the 3D structure of a real scene. In this paper, a novel optimal vanishing point estimation method is proposed. This method detects line segment clustering based on random sample consensus (RANSAC) framework, obtaining the maximum likelihood estimation (MLE) results by minimizing the derived Sampson error. This method is performed without any prior knowledge of the camera parameters or information of underlying 3D lines. The error analysis based on backward propagation method is proceeded to give quantitative evaluation of our estimation algorithm. The physical experiments are carried out to validate the proposed method.
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