Deep Learning KEYSCORE

Deep Learning Glossary

Deep Learning

Feature Descriptors

Feature Descriptors/Vectors

  • Feature descriptors encode interesting information into a series of numbers and act as a sort of numerical “fingerprint” that can be used to differentiate one feature from another.
  • Ideally this information would be invariant under image transformation, so we can find the feature again even if the image is transformed in some way.

BRISK descriptor – BRISK sampling pattern

BRISK descriptor – example of matching points using BRISK

 

Efficient Descriptors

DAISY

SURF (Speeded Up Robust Features)

U-SURF

 

Compact Binary Descriptors

LBP (Local Binary Patterns)

BRIEF

D-BRIEF

ORB (Oriented FAST and Rotated BRIEF)

BRISK (Binary Robust Invariant Scalable Keypoints)

FREAK (Fast Retina Keypoint)

CARD (Compact and Realtime Descriptor)

LDB (Local DIfference Binary)

LDB

More Robust Descriptors

LIOP (Local Intensity Order Pattern for Feature Descriptor)

Learned Descriptors

Winder & Brown

Descriptor Learning Using Convex Optimisation

Learning Spatial Pooling Regions

 

References:

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: