1. 3D map reconstruction using a monocular camera for smart cities.
- Author
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Hu, Yuxi, Fu, Taimeng, Niu, Guanchong, Liu, Zixiao, and Pun, Man-On
- Subjects
SMART cities ,DEEP learning ,MONOCULARS ,GRAPHICS processing units ,CAMERAS ,COMPUTATIONAL complexity - 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. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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