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Context-aware obstacle detection for navigation by visually impaired

Gharani, P and Karimi, HA (2017) Context-aware obstacle detection for navigation by visually impaired. Image and Vision Computing, 64. 103 - 115. ISSN 0262-8856

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This paper presents a context-aware smartphone-based based visual obstacle detection approach to aid visually impaired people in navigating indoor environments. The approach is based on processing two consecutive frames (images), computing optical flow, and tracking certain points to detect obstacles. The frame rate of the video stream is determined using a context-aware data fusion technique for the sensors on smartphones. Through an efficient and novel algorithm, a point dataset on each consecutive frames is designed and evaluated to check whether the points belong to an obstacle. In addition to determining the points based on the texture in each frame, our algorithm also considers the heading of user movement to find critical areas on the image plane. We validated the algorithm through experiments by comparing it against two comparable algorithms. The experiments were conducted in different indoor settings and the results based on precision, recall, accuracy, and f-measure were compared and analyzed. The results show that, in comparison to the other two widely used algorithms for this process, our algorithm is more precise. We also considered time-to-contact parameter for clustering the points and presented the improvement of the performance of clustering by using this parameter.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Gharani, P
Karimi, HAhkarimi@pitt.eduHKARIMI0000-0001-5331-5004
Date: 1 August 2017
Date Type: Publication
Journal or Publication Title: Image and Vision Computing
Volume: 64
Page Range: 103 - 115
DOI or Unique Handle: 10.1016/j.imavis.2017.06.002
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 0262-8856
Date Deposited: 30 Jun 2017 15:02
Last Modified: 30 Mar 2021 10:55


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