Human Skeleton Detection from Semi-constrained Environment Video

Palwasha Afsar, Paulo Cortez, Henrique Santos

Abstract

The correct classification of human skeleton from video is a key issue for the recognition of human actions and behavior. In this paper, we present a computational system for a passive detection of human star skeleton from raw video. The overall system is based on two main modules: segmentation and star skeleton detection. For each module, several computer vision methods were adjusted and tested under a comparative analysis that used a challenging video dataset (e.g., different daylight and weather conditions). The obtained results show that our system is capable of detecting human skeletons in most situations.

References

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Paper Citation


in Harvard Style

Afsar P., Cortez P. and Santos H. (2017). Human Skeleton Detection from Semi-constrained Environment Video . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-226-4, pages 384-389. DOI: 10.5220/0006245803840389


in Bibtex Style

@conference{visapp17,
author={Palwasha Afsar and Paulo Cortez and Henrique Santos},
title={Human Skeleton Detection from Semi-constrained Environment Video},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={384-389},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006245803840389},
isbn={978-989-758-226-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)
TI - Human Skeleton Detection from Semi-constrained Environment Video
SN - 978-989-758-226-4
AU - Afsar P.
AU - Cortez P.
AU - Santos H.
PY - 2017
SP - 384
EP - 389
DO - 10.5220/0006245803840389