Action recognition based on semantic feature description and cross classification

Yang Zhao, Qi Wang, Yuan Yuan

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

1 Scopus citations

Abstract

Action recognition is a challenging topic in computer vision. In this work, we present a novel method for action recognition which is based on two claimed contributions: semantic feature description and cross classification. The designed descriptor is combined by several local 3D-SIFT and is informative and distinctive, reflecting the spatiooral clues of the video. The cross classification effectively combines the feature localization and action categorization together. The proposed method is justified on a popular dateset named UCF50 and the experimental results demonstrate that our method outperforms the state-of-the-art competitors.

Original languageEnglish
Title of host publication2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages626-630
Number of pages5
ISBN (Electronic)9781479954032
DOIs
StatePublished - 3 Sep 2014
Event2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Xi'an, China
Duration: 9 Jul 201413 Jul 2014

Publication series

Name2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

Conference

Conference2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014
Country/TerritoryChina
CityXi'an
Period9/07/1413/07/14

Keywords

  • 3DSIFT
  • action recognition
  • cross classification
  • semantic feature

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