Abstract
In this paper we introduce a 3-dimensional (3D) SIFT descriptor for video or 3D imagery such as MRI data. We also show how this new descriptor is able to better represent the 3D nature of video data in the application of action recognition. This paper will show how 3D SIFT is able to outperform previously used description methods in an elegant and efficient manner. We use a bag of words approach to represent videos, and present a method to discover relationships between spatio-temporal words in order to better describe the video data.
Keywords
Scale-invariant feature transformComputer scienceArtificial intelligenceAction recognitionAction (physics)Pattern recognition (psychology)Bag-of-words modelComputer visionImage (mathematics)
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Publication Info
- Year
- 2007
- Type
- article
- Pages
- 357-360
- Citations
- 1611
- Access
- Closed
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Cite This
Paul Scovanner,
Saad Ali,
Mubarak Shah
(2007).
A 3-dimensional sift descriptor and its application to action recognition.
, 357-360.
https://doi.org/10.1145/1291233.1291311
Identifiers
- DOI
- 10.1145/1291233.1291311