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2018 | OriginalPaper | Buchkapitel

Silhouette-Based Human Action Recognition by Embedding HOG and PCA Features

verfasst von : A. S. Jahagirdar, M. S. Nagmode

Erschienen in: Intelligent Computing and Information and Communication

Verlag: Springer Singapore

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Abstract

Human action recognition has become vital aspect of video analytics. This study explores methods for the classification of human actions by extracting silhouette of object and then applying feature extraction. The method proposes to integrate HOG feature and PCA feature effectively to form a feature descriptor which is used further to train KNN classifier. HOG gives local shape-oriented variations of the object while PCA gives global information about frequently moving parts of human body. Experiments conducted on Weizmann and KTH datasets show results comparable with existing methods.

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Metadaten
Titel
Silhouette-Based Human Action Recognition by Embedding HOG and PCA Features
verfasst von
A. S. Jahagirdar
M. S. Nagmode
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Intelligent Computing and Information and Communication

Print ISBN: 978-981-10-7244-4

Electronic ISBN: 978-981-10-7245-1

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-7245-1_36