Continuous Hand Gesture Recognition using Deep Coarse and Fine Hand Features - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Continuous Hand Gesture Recognition using Deep Coarse and Fine Hand Features

Résumé

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.
Fichier principal
Vignette du fichier
BMVC2022-ContinuousHandGesture.pdf (672.72 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03982987 , version 1 (10-02-2023)

Identifiants

  • HAL Id : hal-03982987 , version 1

Citer

Hazem Wannous, Jean-Philippe Vandeborre. Continuous Hand Gesture Recognition using Deep Coarse and Fine Hand Features. The 33rd British Machine Vision Conference – BMVC 2022, Nov 2022, London, United Kingdom. ⟨hal-03982987⟩
61 Consultations
157 Téléchargements

Partager

Gmail Facebook X LinkedIn More