SIFT stands for Scale Invariant Feature Transform, it is a feature extraction method (among others, such as HOG feature extraction) where image content is transformed into local feature coordinates that are invariant to translation, scale and other image transformations.
Below are the advantages of SIFT:
- Locality: Features are local; robust to occlusion and clutter.
- Distinctiveness: Individual features extracted can be matched to a large dataset of objects.
- Quantity: Using SIFT, we can extract many features from small objects.
- Efficiency: SIFT is close to real-time performance.