Facing the sparse LiDAR (light detecting and ranging) data of the New Orleans area in America，a new residential building model reconstruction method is proposed.The main contributions of this work are the automatic isolation of roof points and the roof type recognition.Using the minimum bounding contour to describe the outline of residential buildings，we are able to automatically identify individual buildings from clustered residential areas.Then，based on the relationship of normal vectors，building types are recognized； through model matching，the buildings models are reconstructed.Experiments show that our method can successfully reconstruct residential buildings given relatively sparse LiDAR samples in a reasonably short time.