1. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 Sensor platform composed of LiDAR Velodyne HDL-64E (L) Ladybug2 (LB) and GPS. Ladybug2 spherical digital video camera system has six cameras (C i ). [R,T]LCi represents rotation and translation of the LiDAR and six camera frames of the Ladybug2. Figure Legend:

2. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 LiDAR framework L and the multicamera system C1,…,C5. [R,T]WCi represents the world-camera transformation, [R,T]WL represents the world-LiDAR transformation, and [R,T]LCi represents the LiDAR-camera transformation. Figure Legend:

3. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 LiDAR Velodyne HDL-64E configuration Figure Legend:

4. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 Tsai's calibration method analyzed by Sobol technique: blue bars are the global sensitivity (S i ) and red bars are the total sensitivity (Sitot). Simulated data by MC and LHS with six different distributions. The most relevant parameters are tz and β, i.e., with more sensitive. Parameter identification is indicated in Table 2. (a) Sobol sequence by MC, (b) Halton sequence by MC, (c) normal distribution by MC, (d) normal distribution by LHS, (e) uniform distribution by LHS, and (f) multivariate distribution by LHS. (See online version for color.) Figure Legend:

5. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 Zhang's calibration method analyzed by Sobol technique: blue bars are the global sensitivity (S i ) and red bars are the total sensitivity (Sitot). Simulated data by MC and LHS with six different distributions. The most relevant parameters are tz and β, i.e., with more sensitive. Parameter identification is indicated in Table 2. (a) Sobol sequence by MC, (b) Halton sequence by MC, (c) normal distribution by MC, (d) normal distribution by LHS, (e) uniform distribution by LHS, and (f) multivariate distribution by LHS. (See online version for color.) Figure Legend:

6. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 Experimental camera calibration results. Twenty sets of images were taken. For each set, our calibration algorithms were run 100 times. The left side of the graphs displays the average per parameter calibrated (dashed line). The right side shows the variability of these results (chain line). The greater the variability, the greater the sensitivity. The tz − ty and α−β parameters show greater change, similar results to those calculated by the FAST and Sobol techniques. Figure Legend:

7. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 LiDAR sensitivity analysis by Sobol method: blue bars are the global sensitivity (S i ) and red bars are the total sensitivity (Sitot). Simulated data by MC and LHS with six different distributions. The most relevant parameters are θ and Δθ. Parameter identification is indicated in Table 3. (a) Sobol sequence by MC, (b) Halton sequence by MC, (c) normal distribution by MC, (d) normal distribution by LHS, (e) uniform distribution by LHS, and (f) multivariate distribution by LHS. Figure Legend:

8. Date of download: 6/9/2016 Copyright © ASME. All rights reserved. From: Complete Sensitivity Analysis in a LiDAR-Camera Calibration Model J. Comput. Inf. Sci. Eng. 2015;16(1):014501-014501-10. doi:10.1115/1.4032026 Experimental LiDAR results. The left side of the graphs shows the average of each laser to calibrate 100 datasets (dashed line). The right side shows the variability of these results (chain line). The greater the variability, the greater the sensitivity. The Δvosc−Δθ parameters show greater change, similar results to those calculated by FAST and Sobol techniques. Figure Legend: