Dynamic hand gesture recognition based on textural features

被引：3

作者：

Agab, Salah Eddine ^{[1
]}

Chelali, Fatma Zohra ^{[1
]}

机构：

[1] Univ Sci & Technol Houari Boumediene USTHB, Fac Elect & Comp Sci, Speech Commun & Signal Proc Lab, Box 32 El Alia, Algiers 16111, Algeria

来源：

2019 INTERNATIONAL CONFERENCE ON ADVANCED ELECTRICAL ENGINEERING (ICAEE) | 2019年

关键词：

LBP; LBPriu2; CS-LBP; EHD; Neural network; MLP; RBF; hand gesture recognition; CLASSIFICATION;

D O I：

10.1109/icaee47123.2019.9014683

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This article proposes an implementation of a dynamic gesture recognition system using different textural descriptors such as the basic Local Binary Patterns (LBP), Rotation Invariant and Uniform LBP (LBPriu2), Center-Symmetric LBP (CS-LBP) and Edge Histogram Descriptor (EHD). The recognition task is performed using two variants of the Artificial Neural Network (ANN), which are the Multilayer Perceptron (MLP) and the Radial Basis Function neural network (RBF). Experiments were performed on a user-independent database with a simple background where 95.83% recognition rate was achieved. A comparison with previous works shows the efficiency of our system.

引用

页数：6

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