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Authors: Hiroki Mori ; Takaomi Kanda ; Dai Hirose and Minoru Asada

Affiliation: Osaka University, Japan

ISBN: 978-989-758-076-5

Keyword(s): 4-Dimensional Pattern Recognition, Higher-order Local Auto-correlation, Point Cloud Time Series, Voxel Time Series, Tesseractic Pattern, IXMAS Dataset.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Feature Selection and Extraction ; Human-Computer Interaction ; Image and Video Analysis ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Software Engineering ; Theory and Methods ; Video Analysis

Abstract: In this paper, we propose a 4-Dimensional Higher-order Local Auto-Correlation (4D HLAC). The method aims to extract the features of a 3D time series, which is regarded as a 4D static pattern. This is an orthodox extension of the original HLAC, which represents correlations among local values in 2D images and can effectively summarize motion in 3D space. To recognize motion in the real world, a recognition system should exploit motion information from the real-world structure. The 4D HLAC feature vector is expected to capture representations for general 3D motion recognition, because the original HLAC performed very well in image recognition tasks. Based on experimental results showing high recognition performance and low computational cost, we conclude that our method has a strong advantage for 3D time series recognition, even in practical situations.

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Paper citation in several formats:
Mori, H.; Kanda, T.; Hirose, D. and Asada, M. (2015). 3-Dimensional Motion Recognition by 4-Dimensional Higher-order Local Auto-correlation.In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 223-231. DOI: 10.5220/0005200602230231

@conference{icpram15,
author={Hiroki Mori. and Takaomi Kanda. and Dai Hirose. and Minoru Asada.},
title={3-Dimensional Motion Recognition by 4-Dimensional Higher-order Local Auto-correlation},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={223-231},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005200602230231},
isbn={978-989-758-076-5},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - 3-Dimensional Motion Recognition by 4-Dimensional Higher-order Local Auto-correlation
SN - 978-989-758-076-5
AU - Mori, H.
AU - Kanda, T.
AU - Hirose, D.
AU - Asada, M.
PY - 2015
SP - 223
EP - 231
DO - 10.5220/0005200602230231

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