Continuous Hand Gesture Recognition using ...
Document type :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Title :
Continuous Hand Gesture Recognition using Deep Coarse and Fine Hand Features
Author(s) :
Wannous, Hazem [Auteur correspondant]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Vandeborre, Jean Philippe [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Vandeborre, Jean Philippe [Auteur]

Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Conference title :
The 33rd British Machine Vision Conference – BMVC 2022
City :
London
Country :
Royaume-Uni
Start date of the conference :
2022-11-21
HAL domain(s) :
Informatique [cs]
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
English abstract : [en]
Using hand gestures as a HCI modality introduces intuitive and easy-to-use interfaces for a wide range of applications. However, the hand is an object with a high number of degrees of freedom and with high similarities ...
Show more >Using hand gestures as a HCI modality introduces intuitive and easy-to-use interfaces for a wide range of applications. However, the hand is an object with a high number of degrees of freedom and with high similarities derived from the heterogeneities of possible gestures. Moreover, the online detection of a gesture as soon as it happens in a video stream is a very challenging problem. To address these difficulties, we introduce an effective deep learning based approach, which takes advantage of the combined description of the hand shape and its temporal variation. First, we employ a transfer learning strategy to learn coarse and fine hand features from depth image dataset originally created for hand pose estimation. Then, we model the temporal aspect separately of the hand poses and its shape variations over the time using recurrent models, before merging. Our approach achieve significant performance for the task of hand gesture detection and recognition. In online scenario, results show that our approach is able to detect an occurring gesture and to recognize it far before its end, making our system efficient for real-time interactive applications.Show less >
Show more >Using hand gestures as a HCI modality introduces intuitive and easy-to-use interfaces for a wide range of applications. However, the hand is an object with a high number of degrees of freedom and with high similarities derived from the heterogeneities of possible gestures. Moreover, the online detection of a gesture as soon as it happens in a video stream is a very challenging problem. To address these difficulties, we introduce an effective deep learning based approach, which takes advantage of the combined description of the hand shape and its temporal variation. First, we employ a transfer learning strategy to learn coarse and fine hand features from depth image dataset originally created for hand pose estimation. Then, we model the temporal aspect separately of the hand poses and its shape variations over the time using recurrent models, before merging. Our approach achieve significant performance for the task of hand gesture detection and recognition. In online scenario, results show that our approach is able to detect an occurring gesture and to recognize it far before its end, making our system efficient for real-time interactive applications.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
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