Human action recognition in video by fusion of structural and spatio-temporal features

Ehsan Zare Borzeshi*, Oscar Perez Concha, Massimo Piccardi

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

The problem of human action recognition has received increasing attention in recent years for its importance in many applications. Local representations and in particular STIP descriptors have gained increasing popularity for action recognition. Yet, the main limitation of those approaches is that they do not capture the spatial relationships in the subject performing the action. This paper proposes a novel method based on the fusion of global spatial relationships provided by graph embedding and the local spatio-temporal information of STIP descriptors. Experiments on an action recognition dataset reported in the paper show that recognition accuracy can be significantly improved by combining the structural information with the spatio-temporal features.

Original languageEnglish
Title of host publicationStructural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings
EditorsGeorgy Gimel'farb, Edwin Hancock, Atsushi Imiya, Arjan Kuijper, Mineichi Kudo, Shinichiro Omachi, Terry Windeatt, Keiji Yamada
Place of PublicationHiroshima, Japan
PublisherSpringer, Springer Nature
Pages474-482
Number of pages9
Volume7626 LNCS
ISBN (Electronic)9783642341663
ISBN (Print)9783642341656
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventJoint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012 - Hiroshima, Japan
Duration: 7 Nov 20129 Nov 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7626 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherJoint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012
CountryJapan
CityHiroshima
Period7/11/129/11/12

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