Algorithm 1: Pseudocode of objective function definition

Input: Point cloud edges data, camera image edges data, calibration parameters. Output: Objective function value. 1. Initialize a pixel coordinates pool $\mathit{P}\mathit{o}\mathit{o}\mathit{l}$ to store the pixel coordinates that have already contributed in the objective function calculation, initialize the objective function value as $\mathit{O}\mathit{b}\mathit{j}$. 2. Use the calibration parameters to project the point cloud edges data onto the camera image plane, which results in a list containing the corresponding pixel coordinates ${\mathit{L}\mathit{i}\mathit{s}\mathit{t}}_{\mathit{P}}$. for pixel $(\mathit{x},\mathit{y})$ in ${\mathit{L}\mathit{i}\mathit{s}\mathit{t}}_{\mathit{P}}$ do 3. if $(\mathit{x},\mathit{y})$ not in $\mathit{P}\mathit{o}\mathit{o}\mathit{l}$ then Add the pixel value with coordinate $(\mathit{x},\mathit{y})$ in the camera image edges data ${\mathit{I}}_{\mathit{c}}\left(\mathit{x},\mathit{y}\right)$ to the objective function value $\mathit{O}\mathit{b}\mathit{j}$. Add the coordinate $(\mathit{x},\mathit{y})$ into the pool $\mathit{P}\mathit{o}\mathit{o}\mathit{l}$. 4. Return the objective function value $\mathit{O}\mathit{b}\mathit{j}$.