A Riemannian Framework for Analysis of Human Body Surface

Pierson, Emery; Daoudi, Mohamed; Tumpach, Alice-Barbara

Document type :

Communication dans un congrès avec actes

Title :

A Riemannian Framework for Analysis of Human Body Surface

Author(s) :

Pierson, Emery [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Daoudi, Mohamed [Auteur]

Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Tumpach, Alice-Barbara [Auteur]
Wolfgang Pauli Institute [WPI]
Laboratoire Paul Painlevé - UMR 8524 [LPP]

Conference title :

Winter Conference on Applications of Computer Vision

City :

HAWAII

Country :

Etats-Unis d'Amérique

Start date of the conference :

2022-01-04

HAL domain(s) :

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

English abstract : [en]

We propose a novel framework for comparing 3D human shapes under the change of shape and pose. This problem is challenging since 3D human shapes vary significantly across subjects and body postures. We solve this problem ...
Show more >We propose a novel framework for comparing 3D human shapes under the change of shape and pose. This problem is challenging since 3D human shapes vary significantly across subjects and body postures. We solve this problem by using a Riemannian approach. Our core contribution is the mapping of the human body surface to the space of metrics and normals. We equip this space with a family of Riemannian metrics, called Ebin (or DeWitt) metrics. We treat a human body surface as a point in a "shape space" equipped with a family of Riemmanian metrics. The family of metrics is invariant under rigid motions and reparametrizations; hence it induces a metric on the "shape space" of surfaces. Using the alignment of human bodies with a given template, we show that this family of metrics allows us to distinguish the changes in shape and pose. The proposed framework has several advantages. First, we define family of metrics with desired invariant properties for the comparison of human shape. Second, we present an efficient framework to compute geodesic paths between human shape given the chosen metric. Third, this framework provides some basic tools for statistical shape analysis of human body surfaces. Finally, we demonstrate the utility of the proposed framework in pose and shape retrieval of human body.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Human4D: Acquisition, Analyse et Synthèse de la Forme du Corps Humain en Mouvement
ULNE

Collections :

Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL

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