# FMT: Unsupervised RGB-D Point Cloud Registration via Fusion Feature Matching with Transformer
## 4 Experiments, Results, and Ablation Study
### Ablation Study  
In Table 5, we analyze the effectiveness of each proposed component by comparing our complete model with partial models, specifically the self-attention layer (S), positional encoding (PE), and self- and cross-attention (SC). We trained all models based on 3 DMatch [20] and tested them on frame Apart of 20. The research findings indicate that the individual use of any one of the three modules did not significantly enhance model performance. Incorporating only the self-attention layer in the fusion module to capture global information slightly reduced performance. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & \multirow{2}{*}{**Train Set**} & \multirow{2}{*}{**Frames Apart**} & \multicolumn{4}{c}{**Rotation (reg)**} & \multicolumn{4}{c}{**Translation (cm)**} \\  & & & \multicolumn{2}{c}{**Accuracy \(\uparrow\)**} & \multicolumn{2}{c}{**Error \(\downarrow\)**} & \multicolumn{2}{c}{**Accuracy \(\uparrow\)**} & \multicolumn{2}{c}{**Error \(\downarrow\)**} \\ \cline{3-12}  & & & **5** & **10** & **45** & **Mean** & **Med.** & **5** & **10** & **25** & **Mean** & **Med.** \\ \hline \multirow{9}{*}{PointMBF [24]} & 3 DMatch & 20 & 94.6 & 96.9 & 99.2 & 2.6 & 0.8 & 79.0 & 91.7 & 97.0 & 5.8 & 2.3 \\  & 3 DMatch & 21 & 93.6 & 96.3 & 99.3 & 2.5 & 0.9 & 78.3 & 90.3 & 96.7 & 6.0 & 2.4 \\  & 3 DMatch & 22 & 92.0 & 95.6 & 99.1 & 3.1 & 1.0 & 76.6 & 89.0 & 95.5 & 7.3 & 2.4 \\  & 3 DMatch & 23 & 91.5 & 95.2 & 99.0 & 3.2 & 1.0 & 74.8 & 87.9 & 95.4 & 7.5 & 2.5 \\  & 3 DMatch & 24 & 91.0 & 94.8 & 98.7 & 3.6 & 1.0 & 73.4 & 87.1 & 94.5 & 8.1 & 2.6 \\  & 3 DMatch & 25 & 89.8 & 94.4 & 98.4 & 3.8 & 1.0 & 71.0 & 85.5 & 93.7 & 9.1 & 2.8 \\  & 3 DMatch & 26 & 88.2 & 93.9 & 98.0 & 4.6 & 1.1 & 70.9 & 84.4 & 93.3 & 10.0 & 2.8 \\  & 3 DMatch & 27 & 88.0 & 93.5 & 97.6 & 4.7 & 1.1 & 68.4 & 83.7 & 93.0 & 10.3 & 2.9 \\  & 3 DMatch & 28 & 86.6 & 92.0 & 97.8 & 5.1 & 1.1 & 66.3 & 82.8 & 92.0 & 11.3 & 3.0 \\  & 3 DMatch & 29 & 84.8 & 91.3 & 97.2 & 5.5 & 1.2 & 66.1 & 81.4 & 90.9 & 11.9 & 3.1 \\  & 3 DMatch & 30 & 84.0 & 90.5 & 96.7 & 6.3 & 1.2 & 63.6 & 79.1 & 90.3 & 13.7 & 3.3 \\ \hline \multirow{9}{*}{ours} & 3 DMatch & 20 & 95.5 & 97.9 & 99.6 & 1.9 & 0.8 & 81.5 & 92.6 & 97.7 & 4.8 & 2.2 \\  & 3 DMatch & 21 & 94.7 & 97.6 & 99.4 & 2.3 & 0.9 & 80.6 & 92.4 & 97.6 & 5.4 & 2.3 \\  & 3 DMatch & 22 & 93.9 & 96.9 & 99.2 & 2.7 & 0.9 & 78.4 & 90.8 & 97.0 & 6.1 & 2.4 \\  & 3 DMatch & 23 & 93.6 & 96.3 & 99.2 & 2.7 & 0.9 & 77.8 & 89.7 & 96.4 & 6.7 & 2.4 \\  & 3 DMatch & 24 & 92.0 & 96.1 & 99.2 & 3.0 & 1.0 & 75.7 & 88.4 & 95.6 & 7.0 & 2.5 \\  & 3 DMatch & 25 & 90.9 & 95.1 & 98.7 & 3.5 & 1.0 & 73.8 & 87.4 & 94.9 & 8.1 & 2.6 \\  & 3 DMatch & 26 & 90.5 & 95.2 & 98.6 & 3.7 & 1.1 & 72.8 & 86.7 & 94.7 & 8.3 & 2.6 \\  & 3 DMatch & 27 & 90.0 & 94.3 & 97.8 & 4.4 & 1.1 & 71.1 & 86.2 & 93.9 & 9.2 & 2.8 \\  & 3 DMatch & 28 & 88.6 & 93.0 & 97.9 & 4.6 & 1.1 & 71.3 & 85.4 & 93.4 & 10.2 & 2.9 \\  & 3 DMatch & 29 & 87.7 & 92.8 & 97.7 & 5.0 & 1.2 & 68.8 & 83.9 & 92.8 & 10.6 & 3.0 \\  & 3 DMatch & 30 & 86.8 & 91.7 & 97.6 & 5.8 & 1.1 & 65.4 & 82.4 & 91.5 & 12.6 & 3.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance comparison on rotation and translation error with different frames apart.