@inproceedings{e749f2e168824ab7a23ec3cdd8a41e71,
title = "Functional body mesh representation - A simplified kinematic model",
abstract = "This paper describes Functional Body Mesh a simplified representation of a body kinematic structure intended to form a framework for marker-wise signal processing of recorded motion trajectories of motion capture of virtually any vertebrates. The parent-child and sibling relationships are inferred on a coherence of movement and constancy of distances. There is proposed a GMM based method for inferring FBM segments from the raw motion capture data based on a relationship between the points. For creating groups representing specific body parts we propose an incremental multicriterial clustering algorithm employing Gaussian mixture models. To infer body parts hierarchy we propose utilizing a consensus method.",
keywords = "Body analysis, Clustering, Gaussian mixture model, Motion capture",
author = "Przemys{\l}aw Skurowski and Magdalena Pawlyta",
note = "Publisher Copyright: {\textcopyright} 2015 AIP Publishing LLC.; International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 ; Conference date: 22-09-2014 Through 28-09-2014",
year = "2015",
month = mar,
day = "10",
doi = "10.1063/1.4912884",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Simos, \{Theodore E.\} and Simos, \{Theodore E.\} and Simos, \{Theodore E.\} and Charalambos Tsitouras",
booktitle = "Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014",
address = "United States",
}