27 October 2013 Similarity-based global optimization of buildings in urban scene
Author Affiliations +
Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89190K (2013) https://doi.org/10.1117/12.2031520
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
In this paper, an approach for the similarity-based global optimization of buildings in urban scene is presented. In the past, most researches concentrated on single building reconstruction, making it difficult to reconstruct reliable models from noisy or incomplete point clouds. To obtain a better result, a new trend is to utilize the similarity among the buildings. Therefore, a new similarity detection and global optimization strategy is adopted to modify local-fitting geometric errors. Firstly, the hierarchical structure that consists of geometric, topological and semantic features is constructed to represent complex roof models. Secondly, similar roof models can be detected by combining primitive structure and connection similarities. At last, the global optimization strategy is applied to preserve the consistency and precision of similar roof structures. Moreover, non-local consolidation is adapted to detect small roof parts. The experiments reveal that the proposed method can obtain convincing roof models and promote the reconstruction quality of 3D buildings in urban scene.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Quansheng Zhu, Quansheng Zhu, Jing Zhang, Jing Zhang, Wanshou Jiang, Wanshou Jiang, "Similarity-based global optimization of buildings in urban scene", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190K (27 October 2013); doi: 10.1117/12.2031520; https://doi.org/10.1117/12.2031520


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