Gesture recognition based on improved shape context algorithm and Earth Mover's Distance

Li Ling Ma, Cheng Cheng, Shu Fen Zhang, Jun Zheng Wang

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

2 Citations (Scopus)

Abstract

The common shape context algorithm does not have the rotational invariance property, which makes the characteristic extraction accuracy decreased a lot under some circumstances. A new improved shape context algorithm is proposed to solve this problem in this paper. The new algorithm chooses some key points and uses them as reference points, rather than like the traditional way that relies on all the contour information. Such improvement can make the new shape context algorithm rotation-invariant and can also simplify the original algorithm. Besides, another improvement is made in this paper. We combine shape context algorithm with EMD to create a new recognition method. The method is used for gesture recognition, and the experiment result shows that the new method has enhanced the gesture recognition accuracy a lot.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control Conference, CCC 2013
PublisherIEEE Computer Society
Pages3906-3911
Number of pages6
ISBN (Print)9789881563835
Publication statusPublished - 18 Oct 2013
Event32nd Chinese Control Conference, CCC 2013 - Xi'an, China
Duration: 26 Jul 201328 Jul 2013

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference32nd Chinese Control Conference, CCC 2013
Country/TerritoryChina
CityXi'an
Period26/07/1328/07/13

Keywords

  • EMD
  • Gesture Recognition
  • invariance
  • shape context

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