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Action recognition based on kinematic representation of video data

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The local space-time feature is an effective way to represent video data and achieves state-of-the-art performance in action recognition. However, in majority of cases, it only captures the static or dynamic cues of the image sequence. In this paper, we propose a novel kinematic descriptor, namely Static and Dynamic fEature Velocity (SDEV), which models the changes of both static and dynamic information with time for action recognition. It is not only discriminative itself, but also complementary to the existing descriptors, thus leading to more comprehensive representation of actions by their combination. Evaluated on two public databases, i.e. UCF sports and Olympic Sports, the results clearly illustrate the competency of SDEV.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1530-1534
Number of pages5
ISBN (Electronic)9781479957514
DOIs
StatePublished - 28 Jan 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • Action recognition
  • kinematic description
  • motion feature

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