A computer vision system that ensure the autonomous navigation of blind people

Abstract : In this paper we introduce a real-time obstacle recognition framework designed to alert the visually impaired people/blind of their presence and to assist humans to navigate safely, in indoor and outdoor environments, by handling a Smartphone device. Static and dynamic objects are detected using interest points selected based on an image grid and tracked using the multiscale Lucas-Kanade algorithm. Next, we activated an object classification methodology. We incorporate HOG (Histogram of Oriented Gradients) descriptor into the BoVW (Bag of Visual Words) retrieval framework and demonstrate how this combination may be used for obstacle classification in video streams. The experimental results performed on various challenging scenes demonstrate that our approach is effective in image sequence with important camera movement, including noise and low resolution data and achieves high accuracy, while being computational efficient.
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Article dans une revue
E-Health and Bioengineering Conference (EHB), 2013, 2013, pp.1-4
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https://hal.archives-ouvertes.fr/hal-00944808
Contributeur : Ruxandra Tapu <>
Soumis le : mardi 11 février 2014 - 11:28:48
Dernière modification le : mardi 10 octobre 2017 - 11:22:03

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  • HAL Id : hal-00944808, version 1

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Ruxandra Tapu, Mocanu Bogdan, Zaharia Titus. A computer vision system that ensure the autonomous navigation of blind people. E-Health and Bioengineering Conference (EHB), 2013, 2013, pp.1-4. 〈hal-00944808〉

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