3D map reconstruction using a monocular camera for smart cities

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Abstract

Large-scale high-resolution three-dimensional (3D) maps play a vital role in the development of smart cities. In this work, a novel deep learning-based multi-view-stereo method is proposed for reconstructing the 3D maps in large-scale urban environments by exploiting a monocular camera. Compared with other existing works, the proposed method can perform 3D depth estimation more efficiently in terms of computational complexity and graphics processing unit memory usage. As a result, the proposed method can practically perform depth estimation for each pixel before generating 3D maps for even large-scale scenes. Extensive experiments on the well-known DTU dataset and real-life data collected on our campus confirm the good performance of the proposed method.

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Hu, Y., Fu, T., Niu, G., Liu, Z., & Pun, M. O. (2022). 3D map reconstruction using a monocular camera for smart cities. Journal of Supercomputing, 78(14), 16512–16528. https://doi.org/10.1007/s11227-022-04512-5

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