Hand gesture recognition based on segmented singular value decomposition

Jing Liu*, Manolya Kavakli

*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.

Original languageEnglish
Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings
EditorsRossitza Setchi, Ivan Jordanov, Robert J. Howlett, Lakhmi C. Jain
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Pages214-223
Number of pages10
Volume6277 LNAI
EditionPART 2
ISBN (Print)3642153895, 9783642153891
DOIs
Publication statusPublished - 2010
Event14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010 - Cardiff, United Kingdom
Duration: 8 Sept 201010 Sept 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6277 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010
Country/TerritoryUnited Kingdom
CityCardiff
Period8/09/1010/09/10

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