Table of Contents

Class MSDDetector

Namespace
Emgu.CV.XFeatures2D
Assembly
Emgu.CV.dll

Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in "Federico Tombari and Luigi Di Stefano. Interest points via maximal self-dissimilarities. In Asian Conference on Computer Vision - ACCV 2014, 2014".

public class MSDDetector : Feature2D, IDisposable, IAlgorithm
Inheritance
MSDDetector
Implements
Inherited Members
Extension Methods

Remarks

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.

Constructors

MSDDetector(int, int, int, int, float, int, float, int, bool)

Create a MSD (Maximal Self-Dissimilarity) keypoint detector.

public MSDDetector(int patchRadius, int searchAreaRadius, int nmsRadius, int nmsScaleRadius, float thSaliency, int kNN, float scaleFactor, int nScales, bool computeOrientation)

Parameters

patchRadius int

Patch radius

searchAreaRadius int

Search area raduis

nmsRadius int

Nms radius

nmsScaleRadius int

Nms scale radius

thSaliency float

Th saliency

kNN int

Knn

scaleFactor float

Scale factor

nScales int

N scales

computeOrientation bool

Compute orientation

Methods

DisposeObject()

Release all the unmanaged resource associated with MSDDetector

protected override void DisposeObject()