Human Action Recognition in Video by Fusion of Structural and Spatio-temporal Features

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 t...

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Bibliographic Details
Published inStructural, Syntactic, and Statistical Pattern Recognition pp. 474 - 482
Main Authors Zare Borzeshi, Ehsan, Perez Concha, Oscar, Piccardi, Massimo
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2012
SeriesLecture Notes in Computer Science
Subjects
Graph
Graph embedding
Human action recognition
Markov models
STIP
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Summary: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.
ISBN:9783642341656
3642341659
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-34166-3_52