Extraction of Roof Feature Lines Based on Geometric Constraints from Airborne LiDAR Data

Airborne LiDAR (Light Detection and Ranging) is an active Earth observing system, which can directly acquire high-accuracy and dense building roof data. Thus, airborne LiDAR has become one of the mainstream source data for building detection and reconstruction. The emphasis for building reconstruction focuses on the accurate extraction of feature lines. Building roof feature lines generally include the internal and external feature lines. Efficient extraction of these feature lines can provide reliable and accurate information for constructing three-dimensional building models. Most related algorithms adopt intersecting the extracted planes fitted by the corresponding points. However, in these methods, the accuracy of feature lines mostly depends on the results of plane extraction. With the development of airborne LiDAR hardware, the point density is enough for accurate extraction of roof feature lines. Thus, after acquiring the results of building detection, this paper proposed a feature lines extraction strategy based on the geometric characteristics of the original airborne LiDAR data, tracking roof outlines, normal ridge lines, oblique ridge lines and valley lines successively. The final refined feature lines can be obtained by normalization. The experimental results showed that our methods can achieve several promising and reliable results with an accuracy of 0.291 m in the X direction, 0.295 m in the Y direction and 0.091 m in the H direction for outlines extraction. Further, the internal feature lines can be extracted with reliable visual effects using our method.