Hand Gesture Recognition System Based on Local Binary Pattern Approach for Mobile Devices

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)

Abstract

Since the appearance of mobile devices, gesture recognition is being a challenging task in the field of computer vision. In this paper, a simple and fast algorithm for static hand gesture recognition for mobile device is described. The hand pose is recognized by using gentle AdaBoost learning algorithm and Local Binary Pattern features. The system is developed on an Android OS platform. The method used consists of two steps: a real-time gesture captured by a smartphone’s camera and the recognition of the hand gestures. It presents a system based on a real-time hand posture recognition algorithm for mobile devices. The aim of this work is to allow the mobile device interpreting the sign made by the user without the need to touch the screen. In this system, the device is able to perform all necessary steps to recognize hand posture without the need to connect to any distant device.

Keywords

Hand posture recognition Android LBP AdaBoost Human-machine interaction 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Houssem Lahiani
    • 1
    • 3
    • 4
  • Monji Kherallah
    • 2
  • Mahmoud Neji
    • 3
    • 4
  1. 1.National School of Electronics and TelecommunicationsUniversity of SfaxSfaxTunisia
  2. 2.Faculty of SciencesUniversity of SfaxSfaxTunisia
  3. 3.Faculty of Economics and ManagementUniversity of SfaxSfaxTunisia
  4. 4.Multimedia Information Systems and Advanced Computing LaboratorySfaxTunisia

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