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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.
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Paul Scovanner
University of Central Florida
Saad Ali
University of Liberia
Mubarak Shah
University of Central Florida
Journal of International Crisis and Risk Communication Research
University of Central Florida
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Scovanner et al. (Sat,) studied this question.
synapsesocial.com/papers/6a08fc952142fc3a3073afe0 — DOI: https://doi.org/10.1145/1291233.1291311