Path-following based Point Matching using Similarity Transformation
This is an incremental improvement for computer vision and robotics applications involving 3D point cloud alignment.
The paper tackled 3D point matching with unknown poses by adapting a path-following method to use similarity transformation instead of affine transformation, resulting in more constrained and robust matching as demonstrated in experiments.
To address the problem of 3D point matching where the poses of two point sets are unknown, we adapt a recently proposed path following based method to use similarity transformation instead of the original affine transformation. The reduced number of transformation parameters leads to more constrained and desirable matching results. Experimental results demonstrate better robustness of the proposed method over state-of-the-art methods.