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Markerless Localization for Blind Users Using Computer Vision and Particle Swarm Optimization

  • Hashem Tamimi
  • Anas Sharabati
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)

Abstract

In this paper, we propose a novel approach, which aims to solve the localization and target-finding problem for blind and partially sighted people. A guidance system, solely implemented on a mobile phone with a camera, is employed. A computer vision approach integrated with Particle Swarm Optimization (PSO) is proposed for tracking the location. Using PSO leads to many advantages: first, it is possible to obtain robust localization results by combining the current and historical information about the location of the blind person. Second, it helps the system to resolve from ambiguous situations caused by facing similar images at different locations. Third, it can detect and recover from cases where the calculated location is wrong. Experimental results show that the proposed method works efficiently because of the simplicity of the approach, which makes it suitable for mobile applications.

Keywords

Particle Swarm Optimization Mobile Phone Mobile Robot Color Histogram Scale Invariant Feature Transform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hashem Tamimi
    • 1
  • Anas Sharabati
    • 1
  1. 1.Information Technology Department, College of Administrative Sciences and InformaticsPalestine Polytechnic UniversityHebron

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