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A quality prediction method is proposed to evaluate the quality of the automatic reconstruction of building models. In this study,\udLiDAR data and topographic maps are integrated for building model reconstruction. Hence, data registration is a critical step for\uddata fusion. To improve the efficiency of the data fusion, a robust least squares method is applied to register boundary points\udextracted from LiDAR data and building outlines obtained from topographic maps. After registration, a quality indicator based on\udthe tensor analysis of residuals is derived in order to evaluate the correctness of the automatic building model reconstruction. Finally,\udan actual dataset demonstrates the quality of the predictions for automatic model reconstruction. The results show that our method\udcan achieve reliable results and save both time and expense on model reconstruction

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

TENSOR-BASED QUALITY PREDICTION FOR BUILDING MODEL RECONSTRUCTION FROM LIDAR DATA AND TOPOGRAPHIC MAP