Editing Scale-invariant feature transform (section)

=== 3D SIFT-like descriptors for human action recognition ===
Extensions of the SIFT descriptor to 2+1-dimensional spatio-temporal data in context of [[human action recognition]] in video sequences have been studied.<ref name="Flitton2010" /><ref name="Laptev2004" /><ref name="Laptev2007" /><ref name="Scovanner2007" /> The computation of local position-dependent histograms in the 2D SIFT algorithm are extended from two to three dimensions to describe SIFT features in a spatio-temporal domain. For application to human action recognition in a video sequence, sampling of the training videos is carried out either at spatio-temporal interest points or at randomly determined locations, times and scales. The spatio-temporal regions around these interest points are then described using the 3D SIFT descriptor. These descriptors are then clustered to form a spatio-temporal [[Bag of words model]]. 3D SIFT descriptors extracted from the test videos are then matched against these ''words'' for human action classification.

The authors report much better results with their 3D SIFT descriptor approach than with other approaches like simple 2D SIFT descriptors and Gradient Magnitude.<ref name="Niebles2006" />