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Construction Management

Analysis of accuracy factor and pre-processing methodology of image compensation for 3D reconstruction using 2D image obtained from unmanned aerial vehicle (UAV)

, , , , &
Pages 2081-2094 | Received 07 Jan 2021, Accepted 18 Aug 2021, Published online: 06 Dec 2021

Figures & data

Figure 1. Input 2D image, calculation of camera pose, generation of 3D point cloud.

Figure 1. Input 2D image, calculation of camera pose, generation of 3D point cloud.

Figure 2. Image histogram process.

Figure 2. Image histogram process.

Figure 3. Image compensation methodologies.

Figure 3. Image compensation methodologies.

Figure 4. Specification of UAV and camera.

Figure 4. Specification of UAV and camera.

Figure 5. Comparison of photogrammetry software.

Figure 5. Comparison of photogrammetry software.

Figure 6. Pre-processing software (Matlab).

Figure 6. Pre-processing software (Matlab).

Figure 7. Test condition(target1(left), target2(right)).

Figure 7. Test condition(target1(left), target2(right)).

Figure 8. Compensation of 2D images.

Figure 8. Compensation of 2D images.

Figure 9. The results of sparse point cloud.

Figure 9. The results of sparse point cloud.

Figure 10. The results of dense point cloud.

Figure 10. The results of dense point cloud.

Table 1. Application possibilities for digital twin.

Table 2. Comparison of sparse point cloud number according to pre-processing variables.

Table 3. Paired sample T-test between original 2D images and compensated 2D images.