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POS, integrated by GPS / INS (Inertial Navigation Systems), has allowed rapid and accurate determination of position and attitude of\udremote sensing equipment for MMS (Mobile Mapping Systems). However, not only does INS have system error, but also it is very\udexpensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS\udin some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the\udtraditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line\udclusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC\ud(Random Sample Consensus) and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to\udestimate nonlinear error equations of two vanishing points (VX, VY). How to set initial weights for the adjustment solution of single\udimage vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with\udvariable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing\udpoints (VX, VY) and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third\udvanishing point (VZ) is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte\udCarlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate\udand their error distributions are shown and analyzed

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

ERROR DISTRIBUTION EVALUATION OF THE THIRD VANISHING POINT BASED ON RANDOM STATISTICAL SIMULATION