M5AIE - A Method for Body Part Detection and Tracking using RGB-D Images

Andre Brandao, Leandro A. F. Fernandes, Esteban Clua

2014

Abstract

The automatic detection and tracking of human body parts in color images is highly sensitive to appearance features such as illumination, skin color and clothes. As a result, the use of depth images has been shown to be an attractive alternative over color images due to its invariance to lighting conditions. However, body part detection and tracking is still a challenging problem, mainly because the shape and depth of the imaged body can change depending on the perspective. We present a hybrid approach, called M5AIE, that uses both color and depth information to perform body part detection, tracking and pose classification. We have developed a modified Accumulative Geodesic Extrema (AGEX) approach for detecting body part candidates. We also have used the Affine-SIFT (ASIFT) algorithm for feature extraction, and we have adapted the conventional matching method to perform tracking and labeling of body parts in a sequence of images that has color and depth information. The results produced by our tracking system were used with the C4.5 Gain Ratio Decision Tree, the naïve Bayes and the KNN classification algorithms for the identification of the users pose.

Paper Citation

in Harvard Style

Brandao A., Fernandes L. and Clua E. (2014). M5AIE - A Method for Body Part Detection and Tracking using RGB-D Images . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 367-377. DOI: 10.5220/0004738003670377

in Bibtex Style

@conference{visapp14,
author={Andre Brandao and Leandro A. F. Fernandes and Esteban Clua},
title={M5AIE - A Method for Body Part Detection and Tracking using RGB-D Images},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={367-377},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004738003670377},
isbn={978-989-758-003-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - M5AIE - A Method for Body Part Detection and Tracking using RGB-D Images
SN - 978-989-758-003-1
AU - Brandao A.
AU - Fernandes L.
AU - Clua E.
PY - 2014
SP - 367
EP - 377
DO - 10.5220/0004738003670377