3D Hand Gesture Recognition Using a Depth and Skeletal Dataset

Smedt, Quentin De; Wannous, Hazem; Vandeborre, Jean-Philippe; Guerry, J.; Saux, B. Le; Filliat, D.

3D Hand Gesture Recognition Using a Depth and Skeletal Dataset

Files

033-038.pdf (1.71 MB)

Date

2017

Authors

Smedt, Quentin De
Wannous, Hazem
Vandeborre, Jean-Philippe
Guerry, J.
Saux, B. Le
Filliat, D.

Publisher

The Eurographics Association

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.

        @inproceedings{10.2312:3dor.20171049
,
booktitle = {Eurographics Workshop on 3D Object Retrieval
},
editor = {Ioannis Pratikakis and Florent Dupont and Maks Ovsjanikov
},
title = {{3D Hand Gesture Recognition Using a Depth and Skeletal Dataset
}},
author = {Smedt, Quentin De and 
Wannous, Hazem and 
Vandeborre, Jean-Philippe and 
Guerry, J. and 
Saux, B. Le and 
Filliat, D.
},
year = {2017
},
publisher = {The Eurographics Association
},
ISSN = {1997-0471
},
ISBN = {978-3-03868-030-7
},
DOI = {10.2312/3dor.20171049
}
}