A quality prediction method is proposed to evaluate the quality of the automatic reconstruction of building models. In this study, LiDAR data and topographic maps are integrated for building model reconstruction. Hence, data registration is a critical step for data fusion. To improve the efficiency of the data fusion, a robust least squares method is applied to register boundary points extracted from LiDAR data and building outlines obtained from topographic maps. After registration, a quality indicator based on the tensor analysis of residuals is derived in order to evaluate the correctness of the automatic building model reconstruction. Finally, an actual dataset demonstrates the quality of the predictions for automatic model reconstruction. The results show that our method can achieve reliable results and save both time and expense on model reconstruction.
|頁（從 - 到）||437-441|
|期刊||International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives|
|出版狀態||Published - 2012 一月 1|
|事件||22nd Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2012 - Melbourne, Australia|
持續時間: 2012 八月 25 → 2012 九月 1
All Science Journal Classification (ASJC) codes