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.
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Tamimi, H., Sharabati, A. (2010). Markerless Localization for Blind Users Using Computer Vision and Particle Swarm Optimization. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12239-2_38
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DOI: https://doi.org/10.1007/978-3-642-12239-2_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12238-5
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