Literature DB >> 23529106

Intuitive tactile zooming for graphics accessed by individuals who are blind and visually impaired.

Ravi Rastogi1, T V Dianne Pawluk, Jessica Ketchum.   

Abstract

One possibility of providing access to visual graphics for those who are visually impaired is to present them tactually: unfortunately, details easily available to vision need to be magnified to be accessible through touch. For this, we propose an "intuitive" zooming algorithm to solve potential problems with directly applying visual zooming techniques to haptic displays that sense the current location of a user on a virtual diagram with a position sensor and, then, provide the appropriate local information either through force or tactile feedback. Our technique works by determining and then traversing the levels of an object tree hierarchy of a diagram. In this manner, the zoom steps adjust to the content to be viewed, avoid clipping and do not zoom when no object is present. The algorithm was tested using a small, "mouse-like" display with tactile feedback on pictures representing houses in a community and boats on a lake. We asked the users to answer questions related to details in the pictures. Comparing our technique to linear and logarithmic step zooming, we found a significant increase in the correctness of the responses (odds ratios of 2.64:1 and 2.31:1, respectively) and usability (differences of 36% and 19%, respectively) using our "intuitive" zooming technique.

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Year:  2013        PMID: 23529106     DOI: 10.1109/TNSRE.2013.2250520

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  2 in total

1.  Updated Tactile Feedback with a Pin Array Matrix Helps Blind People to Reduce Self-Location Errors.

Authors:  Luca Brayda; Fabrizio Leo; Caterina Baccelliere; Elisabetta Ferrari; Claudia Vigini
Journal:  Micromachines (Basel)       Date:  2018-07-14       Impact factor: 2.891

2.  Efficient Multi-Object Detection and Smart Navigation Using Artificial Intelligence for Visually Impaired People.

Authors:  Rakesh Chandra Joshi; Saumya Yadav; Malay Kishore Dutta; Carlos M Travieso-Gonzalez
Journal:  Entropy (Basel)       Date:  2020-08-27       Impact factor: 2.524

  2 in total

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