Building boundaries are important spatial features that characterize the topographic maps and three-dimensional (3D) city models. Airborne LiDAR Point clouds provide adequate 3D spatial information for building boundary mapping. However, information of boundary features contained in point clouds is implicit. This study focuses on developing an automatic algorithm of building boundary extraction from airborne LiDAR data. Usually top surfaces, such as roofs, may have densely distributed points, but vertical surfaces, such as walls, usually have sparsely distributed points or even no points. The intersections of roof and wall planes are, therefore, not clearly defined in point clouds. Therefore two major process steps are presented in the algorithm to improve the edge extraction from LiDAR data. The first step is to extract building boundary points from point clouds, and then the second step is to form building boundary line features based on the extracted boundary points. The test data in our experiments include a variety of buildings. The experiment results show the effectiveness of the proposed method for automatic building boundary extraction from airborne LiDAR data, and that combining the information of the first and intermediate echo points of multi-return and the boundary points increases the completeness of boundaries. And, it is promising to use the extracted boundaries for 3D building modelling in the future.