Survey on Style in 3D Human Body Motion: Taxonomy, Data, Recognition and its Applications

Ribet, Sarah; Wannous, Hazem; Vandeborre, Jean Philippe

Type de document :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1109/TAFFC.2019.2906167

Titre :

Survey on Style in 3D Human Body Motion: Taxonomy, Data, Recognition and its Applications

Auteur(s) :

Ribet, Sarah [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Wannous, Hazem [Auteur correspondant]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Vandeborre, Jean Philippe [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]

Titre de la revue :

IEEE Transactions on Affective Computing

Pagination :

928-948

Éditeur :

Institute of Electrical and Electronics Engineers

Date de publication :

2021-10

ISSN :

1949-3045

Mot(s)-clé(s) en anglais :

motion
character animation
motion style generation
Motion recognition
motion classification

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

Résumé en anglais : [en]

The meaning of the word style depends on its context. While actions have already been quite studied for a while, style in human body motion is a growing topic of interest. In the context of animation, style is crucial as ...
Lire la suite >The meaning of the word style depends on its context. While actions have already been quite studied for a while, style in human body motion is a growing topic of interest. In the context of animation, style is crucial as it brings realism and expressiveness to the motion of a character. Even though it is undoubtedly a key element in motions, its definition and the use of the word style in itself, among research works, lack consensus. Achieving realistic motions is tedious. It requires either a large motion capture dataset or the considerable work of artist animators. The lack of consistent style data is thus a challenge. Stylistic motion generation is quite studied in order to overcome this issue. This paper focuses on the study of style in human body motion from 3D human body skeletal data. It establishes a taxonomy of definitions of style, describes the data that have been used up until now, introduces key notions about motion capture data as well as machine learning, and presents approaches about style recognition, person identification through their style and motion style generation.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :