Semantic Scholar Open Access 2022 1 sitasi

Pavement Roughness Estimated by RGB-D Sensor Based on Three-Dimensional Reconstruction

Fan Wu Yonghui Feng

Abstrak

The measurement of the pavement roughness and the detection of road defects are two important tasks in highway engineering. In view of the high cost of pavement data collection, this research proposes a method to calculate the pavement roughness by using the economical RGB-D sensor on the mobile terminal through three-dimensional reconstruction. We propose a joint filtering algorithm based on weight judgment for the depth image restoration and a direct method for the pose estimation based on optimizing normalization coefficients of the image blocks. We calculate the pavement roughness through the three-dimensional pavement model generated by point cloud registration. Results show that the method proposed in this paper can accurately calculate the pavement roughness of different roads, and the accuracy is above 90%.

Penulis (2)

Fan Wu

Yonghui Feng

Format Sitasi

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Wu, F., Feng, Y. (2022). Pavement Roughness Estimated by RGB-D Sensor Based on Three-Dimensional Reconstruction. https://doi.org/10.1109/ctisc54888.2022.9849746

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Total Sitasi: 1×
Sumber Database: Semantic Scholar
DOI: 10.1109/ctisc54888.2022.9849746
Akses: Open Access ✓