Building Detection from High Resolution Remote Sensing Imagery Based on a Deformable Part Model

The characteristics of high resolution remote sensing imagery-complex scenes, diversity, various forms of one target, and so on-make automatic building detection difficult.. In recent years, the deformable part model (DPM) has become widely used in the field of pattern recognition, and effective for target recognition in natural scenes. In this paper, we propose a new method of building detection using high resolution remote sensing imagery, based on DPM. This method considers a building as a combination of deformable parts, obtains its template parameters by training, and traverses images with a sliding window to detect buildings. Experiments show the validity of the method.