Projection-based Classification of Surfaces for 3D Human Mesh Sequence Retrieval

Autor: Juan Carlos Álvarez Paiva, Mohamed Daoudi, Emery Pierson
Přispěvatelé: 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), Laboratoire Paul Painlevé (LPP), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Institut Mines-Télécom [Paris] (IMT), ANR-19-CE23-0020,Human4D,Human4D: Acquisition, Analyse et Synthèse de la Forme du Corps Humain en Mouvement(2019), ANR-16-IDEX-0004,ULNE,ULNE(2016), Laboratoire Paul Painlevé - UMR 8524 (LPP), Centre National de la Recherche Scientifique (CNRS)-Université de Lille
Rok vydání: 2021
Předmět:
Zdroj: Computers & Graphics: X
Computers & Graphics: X, 2022, 102 (45-55)
Computers & Graphics: X, 2021, ⟨10.1016/j.cag.2021.10.012⟩
ISSN: 2590-1486
DOI: 10.48550/arxiv.2111.13985
Popis: We analyze human poses and motion by introducing three sequences of easily calculated surface descriptors that are invariant under reparametrizations and Euclidean transformations. These descriptors are obtained by associating to each finitely-triangulated surface two functions on the unit sphere: for each unit vector u we compute the weighted area of the projection of the surface onto the plane orthogonal to u and the length of its projection onto the line spanned by u . The L 2 norms and inner products of the projections of these functions onto the space of spherical harmonics of order k provide us with three sequences of Euclidean and reparametrization invariants of the surface. The use of these invariants reduces the comparison of 3D+time surface representations to the comparison of polygonal curves in R n . The experimental results on the FAUST and CVSSP3D artificial datasets are promising. Moreover, a slight modification of our method yields good results on the noisy CVSSP3D real dataset.
Databáze: OpenAIRE