Ilya Afanasyev, Massimo Lunardelli, Nicolò Biasi, Luca Baglivo, Mattia Tavernini, Francesco Setti, Mariolino De Cecco


This paper presents a method for 3D Human Body pose estimation. 3D real data of the searched object is acquired by a multi-camera system and segmented by a special preprocessing algorithm based on clothing analysis. The human body model is built by nine SuperQuadrics (SQ) with a-priori known anthropometric scaling and shape parameters. The pose is estimated hierarchically by RANSAC-object search with a least square fitting 3D point cloud to SQ models: at first the body, and then the limbs. The solution is verified by evaluating the matching score, i.e. the number of inliers corresponding to a-piori chosen distance threshold, and comparing this score with admissible inlier threshold for the body and limbs. This method can be used for 3D object recognition, localization and pose estimation of Human Body.


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Paper Citation

in Harvard Style

Afanasyev I., Lunardelli M., Biasi N., Baglivo L., Tavernini M., Setti F. and De Cecco M. (2012). 3D HUMAN BODY POSE ESTIMATION BY SUPERQUADRICS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 294-302. DOI: 10.5220/0003862202940302

in Bibtex Style

author={Ilya Afanasyev and Massimo Lunardelli and Nicolò Biasi and Luca Baglivo and Mattia Tavernini and Francesco Setti and Mariolino De Cecco},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},

in EndNote Style

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
SN - 978-989-8565-04-4
AU - Afanasyev I.
AU - Lunardelli M.
AU - Biasi N.
AU - Baglivo L.
AU - Tavernini M.
AU - Setti F.
AU - De Cecco M.
PY - 2012
SP - 294
EP - 302
DO - 10.5220/0003862202940302