Start and End Point Detection of Weightlifting Motion using CHLAC and MRA

Fumito Yoshikawa, Takumi Kobayashi, Kenji Watanabe, Katsuyoshi Shirai, Nobuyuki Otsu

Abstract

Extracting human motion segments of interest in image sequences is essential for quantitative analysis and effective video browsing, although it requires laborious human efforts. In analysis of sport motion such as weightlifting, it is required to detect the start and end of each weightlifting motion in an automated manner and hopefully even for different camera angle-views. This paper describes a weightlifting motion detection method employing cubic higher-order local auto-correlation (CHLAC) and multiple regression analysis (MRA). This method extracts spatio-temporal motion features and leans the relationship between the features and specific motion, without prior knowledge about objects. To demonstrate the effectiveness of our method, the experiment was conducted on data captured from eight different viewpoints in practical situations. The detection rates for the start and end motions were more than 94% for 140 data in total even for different angle views, 100% for some angles.

References

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Paper Citation


in Harvard Style

Yoshikawa F., Kobayashi T., Watanabe K., Shirai K. and Otsu N. (2010). Start and End Point Detection of Weightlifting Motion using CHLAC and MRA . In Proceedings of the 1st International Workshop on Bio-inspired Human-Machine Interfaces and Healthcare Applications - Volume 1: B-Interface, (BIOSTEC 2010) ISBN 978-989-674-020-7, pages 44-50. DOI: 10.5220/0002813100440050


in Bibtex Style

@conference{b-interface10,
author={Fumito Yoshikawa and Takumi Kobayashi and Kenji Watanabe and Katsuyoshi Shirai and Nobuyuki Otsu},
title={Start and End Point Detection of Weightlifting Motion using CHLAC and MRA},
booktitle={Proceedings of the 1st International Workshop on Bio-inspired Human-Machine Interfaces and Healthcare Applications - Volume 1: B-Interface, (BIOSTEC 2010)},
year={2010},
pages={44-50},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002813100440050},
isbn={978-989-674-020-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Bio-inspired Human-Machine Interfaces and Healthcare Applications - Volume 1: B-Interface, (BIOSTEC 2010)
TI - Start and End Point Detection of Weightlifting Motion using CHLAC and MRA
SN - 978-989-674-020-7
AU - Yoshikawa F.
AU - Kobayashi T.
AU - Watanabe K.
AU - Shirai K.
AU - Otsu N.
PY - 2010
SP - 44
EP - 50
DO - 10.5220/0002813100440050