Title :

Analysis of Skeletal Shape Trajectories for Person Re-Identification

Author(s) :

Elaoud, Amani [Auteur]
Université de Tunis El Manar [UTM]
Barhoumi, Walid [Auteur]
Université de Carthage (Tunisie) [UCAR]
Drira, Hassen [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Zagrouba, Ezzeddine [Auteur]
Université de Tunis El Manar [UTM]

Scientific editor(s) :

Jacques Blanc-Talon
Rudi Penne
Wilfried Philips
Dan Popescu
Paul Scheunders

Conference title :

ACIVS 2017 - 18th International Conference on Advanced Concepts for Intelligent Vision Systems

City :

Anvers

Country :

Belgique

Start date of the conference :

2017-09-18

Book title :

Lecture Notes in Computer Science

Journal title :

Advanced Concepts for Intelligent Vision Systems 18th International Conference, ACIVS 2017

Publisher :

Springer

Publication date :

2017

English keyword(s) :

Skeleton information
Similarity evaluation
Person re-identification
RGB-D sensors
Grassmann manifold

HAL domain(s) :

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

English abstract : [en]

In this paper, we are interested in people re-identification using skeleton information provided by a consumer RGB-D sensor. We perform the modelling and the analysis of human motion by focusing on 3D human joints given ...
Show more >In this paper, we are interested in people re-identification using skeleton information provided by a consumer RGB-D sensor. We perform the modelling and the analysis of human motion by focusing on 3D human joints given by skeletons. In fact, the motion dynamic is modeled by projecting skeleton information on Grassmann manifold. Moreover, in order to define the identity of a test trajectory, we compare it against a labeled trajectory database while using an unsupervised similarity assessment procedure. Indeed, the main contribution of this work resides in the introduced distance that combines temporal information as well as global and local geometrical ones. Realized experiments on standard datasets prove that the proposed method performs accurately even though it does not assume any prior knowledge.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL