eprintid: 3758
rev_number: 6
eprint_status: archive
userid: 69
dir: disk0/00/00/37/58
datestamp: 2017-08-04 11:42:06
lastmod: 2017-08-04 11:42:06
status_changed: 2017-08-04 11:42:06
type: conference_item
metadata_visibility: show
creators_name: Kolykhalova, Ksenia
creators_name: Gnecco, Giorgio
creators_name: Sanguineti, Marcello
creators_name: Camurri, Antonio
creators_name: Volpe, Gualtiero
creators_id: 
creators_id: giorgio.gnecco@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
title: Graph-restricted Game Approach for Investigating Human Movement Qualities
ispublished: pub
subjects: QA
subjects: QA75
divisions: CSA
full_text_status: none
pres_type: paper
keywords: Human movement qualities, game theory, graph theory
abstract: A novel computational method for the analysis of expressive full-body movement qualities is introduced, which exploits concepts and tools from graph theory and game theory. The human skeletal structure is modeled as an undirected graph, where the joints are the vertices and the edge set contains both physical and non-physical links. Physical links correspond to connections between adjacent physical body joints (e.g., the forearm, which connects the elbow to the wrist). Nonphysical links act as "bridges" between parts of the body not directly connected by the skeletal structure, but sharing very similar feature values. The edge weights depend on features obtained by using Motion Capture data. Then, a mathematical game is constructed over the graph structure, where the vertices represent the players and the edges represent communication channels between them. Hence, the body movement is modeled in terms of a game built on the graph structure. Since the vertices and the edges contribute to the overall quality of the movement, the adopted game-theoretical model is of cooperative nature. A game-theoretical concept, called Shapley value, is exploited as a centrality index to estimate the contribution of each vertex to a shared goal (e.g., to the way a particular movement quality is transferred among the vertices). The proposed method is applied to a data set of Motion Capture data of subjects performing expressive movements, recorded in the framework of the H2020-ICT-2015 EU Project WhoLoDance, Project no. 688865. Preliminary results are presented.
date: 2017
date_type: published
series: MOCO '17
publisher: ACM
place_of_pub: New York, NY, USA
pagerange: 30:1-30:4
event_title: Proceedings of the 4th International Conference on Movement Computing
event_location: London, United Kingdom
event_dates: June 28-30, 2017
event_type: conference
id_number: 10.1145/3077981.3078030
refereed: TRUE
isbn: 978-1-4503-5209-3
book_title: Proceedings of the 4th International Conference on Movement Computing
official_url: http://doi.acm.org/10.1145/3077981.3078030
citation:   Kolykhalova, Ksenia and Gnecco, Giorgio and Sanguineti, Marcello and Camurri, Antonio and Volpe, Gualtiero  Graph-restricted Game Approach for Investigating Human Movement Qualities.  In: Proceedings of the 4th International Conference on Movement Computing, June 28-30, 2017, London, United Kingdom 30:1-30:4.  ISBN 978-1-4503-5209-3.      (2017)