Survey on Style in 3D Human Body Motion: Taxonomy, Data, Recognition and its Applications
| Autor: | Sarah Ribet, Hazem Wannous, Jean-Philippe Vandeborre |
|---|---|
| Přispěvatelé: | Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
character animation
motion style generation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Context (language use) 02 engineering and technology Animation Motion capture Motion (physics) Style (sociolinguistics) motion classification Human-Computer Interaction Motion recognition Human–computer interaction Taxonomy (general) motion 0202 electrical engineering electronic engineering information engineering Character animation 020201 artificial intelligence & image processing Software Meaning (linguistics) ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | IEEE Transactions on Affective Computing IEEE Transactions on Affective Computing, Institute of Electrical and Electronics Engineers, In press, pp.1-1. ⟨10.1109/TAFFC.2019.2906167⟩ IEEE Transactions on Affective Computing, 2021, 12 (4), pp.928-948. ⟨10.1109/TAFFC.2019.2906167⟩ |
| ISSN: | 1949-3045 |
| DOI: | 10.1109/TAFFC.2019.2906167⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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