This paper presents a novel method for automated extraction of building footprints from mobile LIDAR point clouds. We first generate the georeferenced feature image of mobile LIDAR point clouds using an interpolation method

and adopt image segmentation and contour extraction and tracing to extract building boundaries in the geo-referenced feature image as the coarse level of building footprints in Two-dimensional imagery space. Then

the coarse level of building footprints is further refined by applying planar segmentation on the extracted point clouds in the building boundaries. Finally

the triangulated irregular network （TIN） is used to achieve the fine level of building footprints. Dataset of residential areas captured by Optech’s LYNX mobile mapping system was tested to check the validities of the proposed method. Experimental results show that the proposed method provides a promising and valid solution for automatically extracting building footprints from mobile LIDAR point clouds.