Building detection and extraction from monocular imagery by pose clustering and matrix search algorithm
Shiyong Cui, Yan Qin, Zhengjun Liu, Min Li · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
This paper is focused on the task of building extraction from high resolution imagery, which is primarily comprised of two steps. The first one is the building location by modified pose clustering, and the second is building extraction using a novel matrix search algorithm. As a generate-and-test algorithm, pose clustering produces some building hypotheses based on vote accumulation, aimed at image subsets likely to contain just a building. After building hypotheses verification, some false alarms could be eliminated based on geometric rules. Then we focus on image subsets, each of which is a potential region containing a building. Most buildings are comprised of orthogonal and sequential corners. We classify the corners into four types according to the orientation of corresponding edges. Each type of corners is labeled with a tag for identification, such as ABCD, etc. Building contained in each image subset can be represented as a tag sequence. Based on the tag sequence and the matrix formed by the dominate line sets, we develop an efficient matrix searching algorithm to address the task of extraction. The experiments carried out in our system show the promising potential of this scheme.