Algorithm 1 RGB-D SLAM with MFE Using Orientation Relevance

Input: RGB-D sequences Output: Trajectory of RGB-D sensor and reconstructed environment. Step 1. Extract planes from the RGB image using edge detection and triangulation of end points of detected edges. Step 2. Estimate Manhattan Frame using orientation relevance with dominant planes determined by cross validation on depth information and planes extracted from RGB image. Step 3. Determine whether the MFE is available. If it’s available, compute the pairwise spatial transformation with MFE and GICP, and then jump to Step 5. Otherwise, go to Step4. Step 4. Compute the pairwise spatial transformation following the routine of the original RGB-D SLAM. Step 5. Optimize the trajectory. Step 6. Registrate 3D point clouds. Step 7. Voxelize the registrated 3D point clouds. Step 8. Reconstruct the 3D map. return Trajectory and 3D map.