SHREC17 Track: 3D Hand Gesture Recognition Using a Depth and Skeletal DatasetReportar como inadecuado




SHREC17 Track: 3D Hand Gesture Recognition Using a Depth and Skeletal Dataset - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 3D-SAM - Modeling and Analysis of Static and Dynamic Shapes CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 2 IMT Lille Douai 3 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 4 Palaiseau - ONERA - The French Aerospace Lab 5 ENSTA ParisTech U2IS - Unité d-Informatique et d-Ingénierie des Systèmes

Abstract : Hand gesture recognition is recently becoming one of the most attractive field of research in pattern recognition. The objective of this track is to evaluate the performance of recent recognition approaches using a challenging hand gesture dataset containing 14 gestures, performed by 28 participants executing the same gesture with two different numbers of fingers. Two research groups have participated to this track, the accuracy of their recognition algorithms have been evaluated and compared to three other state-of-the-art approaches.

Keywords : Gesture recognition computer graphic machine learning





Autor: Quentin De Smedt - Hazem Wannous - Jean-Philippe Vandeborre - Joris Guerry - Bertrand Le Saux - David Filliat -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados