Similarity-based global optimization of buildings in urban scene

Quansheng Zhu; Jing Zhang; Wanshou Jiang

doi:10.1117/12.2031520

27 October 2013 Similarity-based global optimization of buildings in urban scene

Quansheng Zhu, Jing Zhang, Wanshou Jiang

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

Abstract

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.

Citation Download Citation

Quansheng Zhu, Jing Zhang, and 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); https://doi.org/10.1117/12.2031520

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KEYWORDS

Buildings

3D modeling

Clouds

Data modeling

Optimization (mathematics)

Connectors

Process modeling

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