Trajectories Comparing Based on Matching and Distance Evaluation Within Stiefel and Grassmann Manifolds

Elaoud, Amani; Barhoumi, Walid; Drira, Hassen; Zagrouba, Ezzeddine

Type de document :

Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes

Titre :

Trajectories Comparing Based on Matching and Distance Evaluation Within Stiefel and Grassmann Manifolds

Auteur(s) :

Elaoud, Amani [Auteur]
Université de Tunis El Manar [UTM]
Barhoumi, Walid [Auteur]
Université de Tunis El Manar [UTM]
Drira, Hassen [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Zagrouba, Ezzeddine [Auteur]
Laboratoire de recherche en Génie Logiciel, Applications distribuées, Systèmes décisionnels et Imagerie intelligente [Manouba] [RIADI]

Titre de la manifestation scientifique :

International Conference INFORMATION SYSTEMS IADIS

Ville :

Lisbonne

Pays :

Portugal

Date de début de la manifestation scientifique :

2017

Mot(s)-clé(s) en anglais :

Trajectories
Human Motion
Grassmann
Stiefel
Kinect
manifolds
matching
skeleton

Discipline(s) HAL :

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

Résumé en anglais : [en]

In this paper, we are interested in comparing human trajectories using skeleton information provided by a consumer RGB-D sensor. In fact, 3D human joints given by skeletons offer an important information for human motion ...
Lire la suite >In this paper, we are interested in comparing human trajectories using skeleton information provided by a consumer RGB-D sensor. In fact, 3D human joints given by skeletons offer an important information for human motion analysis. In this context, the use of manifolds has grown considerably in the computer vision community in recent years. The main contribution of this study resides in working jointly with two manifolds. The matching of the trajectories is performed in Stiefel manifold and dissimilarity measure is carried out in Grassmann manifold. Indeed, trajectories of motions are provided by the projection in the Stiefel manifold. Then, the Stiefel distance is used within the dynamic time warping in order to define the appropriate matching between a reference trajectory and a test one. This allows avoiding that the rotation within the motion will be ignored, as it is the case with the Grassmann manifold. Then, the dissimilarity is evaluated using the Grassmann distance to compare motions while being invariant against rotation. Realized experiments on standard challenging datasets prove that the proposed method, for the comparison of human trajectories with different sizes, performs accurately compared to existing manifold-based methods.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL

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