public class MSDDetector
extends Feature2D
Class implementing the MSD (*Maximal Self-Dissimilarity*) keypoint detector, described in CITE: Tombari14.
The algorithm implements a novel interest point detector stemming from the intuition that image patches
which are highly dissimilar over a relatively large extent of their surroundings hold the property of
being repeatable and distinctive. This concept of "contextual self-dissimilarity" reverses the key
paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local
Means filter, which build upon the presence of similar - rather than dissimilar - patches. Moreover,
it extends to contextual information the local self-dissimilarity notion embedded in established
detectors of corner-like interest points, thereby achieving enhanced repeatability, distinctiveness and
localization accuracy.