Topologically Stable Hough Transform
This work addresses line detection in computer vision, offering a novel approach that could improve accuracy or efficiency in applications like image processing, but it appears incremental as it builds on the established Hough transform.
The authors tackled the problem of detecting lines in point clouds by proposing an alternative Hough transform formulation that uses a continuous score function and persistent homology to identify candidate lines, and they developed an efficient algorithm for computation.
We propose an alternative formulation of the well-known Hough transform to detect lines in point clouds. Replacing the discretized voting scheme of the classical Hough transform by a continuous score function, its persistent features in the sense of persistent homology give a set of candidate lines. We also devise and implement an algorithm to efficiently compute these candidate lines.