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Authors: Ivo Reznicek and Pavel Zemcik

Affiliation: Brno University of Technology, Czech Republic

ISBN: 978-989-758-018-5

Keyword(s): Space-time Interest Points, Action Recognition, Real-time Processing, SVM.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Computer Vision, Visualization and Computer Graphics ; Health Engineering and Technology Applications ; Image and Video Analysis ; Image Understanding ; Pattern Recognition ; Signal Processing ; Software Engineering ; Video Analysis

Abstract: Action recognition in video is an important part of many applications. While the performance of action recognition has been intensively investigated, not much research so far has been done in the understanding of how long a sequence of video frames is needed to correctly recognize certain actions. This paper presents a new method of measurement of the length of the video sequence necessary to recognize the actions based on space-time feature points. Such length is the key information necessary to successfully recognize the actions in real-time or performance critical applications. The action recognition used in the presented approach is the state-of-the-art one; vocabulary, bag of words and SVM processing. The proposed methods is experimentally evaluated on human action recognition dataset.

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Paper citation in several formats:
Reznicek, I. and Zemcik , P. (2014). Human Action Recognition for Real-time Applications.In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 646-653. DOI: 10.5220/0004826606460653

@conference{icpram14,
author={Ivo Reznicek. and Pavel Zemcik .},
title={Human Action Recognition for Real-time Applications},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={646-653},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004826606460653},
isbn={978-989-758-018-5},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Human Action Recognition for Real-time Applications
SN - 978-989-758-018-5
AU - Reznicek, I.
AU - Zemcik , P.
PY - 2014
SP - 646
EP - 653
DO - 10.5220/0004826606460653

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