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A 3-dimensional sift descriptor and its application to action recognition

Published:29 September 2007Publication History

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.

References

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  1. A 3-dimensional sift descriptor and its application to action recognition

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        cover image ACM Conferences
        MM '07: Proceedings of the 15th ACM international conference on Multimedia
        September 2007
        1115 pages
        ISBN:9781595937025
        DOI:10.1145/1291233

        Copyright © 2007 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 29 September 2007

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        Overall Acceptance Rate995of4,171submissions,24%

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