LiDAR has been a major interest of photogrammetry to acquire three dimensional objects. It has shown its promising capabilities in building virtual reality applications, such as virtual campus and virtual historic sites. However, point clouds of LiDAR data always occupy a large sum of storage capacity. This blocks further fast processing of LiDAR data to combine with GIS to build virtual reality. The research focused on linear feature extraction of buildings from terrestrial LiDAR data. To obtain linear features of buildings is one of the critical steps to realize minimization of redundant data and high efficiency of data processing. The paper discussed the procedure of linear features extracting of buildings and mainly put forward edge detection algorithms based on fractal dimension theory. Triangular method was chosen to obtain fractal dimension values of grids. The algorithm was not only effective and efficient to detect building edges, but also helpful for segmenting the building and nature objects. Future work was also discussed in the end.