Tensor-based quality prediction for building model reconstruction from lidar data and topographic map

B. C. Lin, R. J. You

研究成果: Conference article同行評審

1 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)437-441
頁數5
期刊International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
39
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 252012 九月 1

All Science Journal Classification (ASJC) codes

  • 資訊系統
  • 地理、規劃與發展

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