Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
INSIDe: Image recognition tool aimed at helping visually impaired people contextualize indoor environments
Federal University of Fronteira Sul, Brazil.
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Federal University of Fronteira Sul, Brazil. (Interaction Lab (ILAB))ORCID iD: 0000-0001-6479-4856
Federal University of Fronteira Sul, Brazil.
Federal University of Rio Grande do Sul, Brazil.
2019 (English)In: Revista Brasileira de Computação Aplicada, ISSN 2176-6649, Vol. 11, no 3, p. 59-71Article in journal (Refereed) Published
Abstract [en]

Visually impaired (VI) people face a set of challenges when trying to orient and contextualize themselves. Computer vision and mobile devices can be valuable tools to help them improve their quality of life. This work presents a tool based on computer vision and image recognition to assist VI people to better contextualize themselves indoors. The tool works as follows: user takes a picture rho using a mobile application; rho is sent to the server; rho is compared to a database of previously taken pictures; server returns metadata of the database image that is most similar to rho; finally the mobile application gives an audio feedback based on the received metadata. Similarity test among database images and rho is based on the search of nearest neighbors in key points extracted from the images by SIFT descriptors. Three experiments are presented to support the feasibility of the tool. We believe our solution is a low cost, convenient approach that can leverage existing IT infrastructure, e.g. wireless networks, and does not require any physical adaptation in the environment where it will be used.

Place, publisher, year, edition, pages
UNIV PASSO FUNDO , 2019. Vol. 11, no 3, p. 59-71
Keywords [en]
Android system, computer vision, SIFT, Visually impaired
National Category
Computer Sciences
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-18024DOI: 10.5335/rbca.v11i3.9455ISI: 000493127600006OAI: oai:DiVA.org:his-18024DiVA, id: diva2:1380842
Available from: 2019-12-19 Created: 2019-12-19 Last updated: 2020-01-29Bibliographically approved

Open Access in DiVA

fulltext(3777 kB)200 downloads
File information
File name FULLTEXT02.pdfFile size 3777 kBChecksum SHA-512
d0864de1676813135fa38ac13457f32f91e16e37fdad1a6f0411fc6af88153d7c27965397c70945a9448d8b17d80606f31edd40d10b5e805bd5d05a84c37eb7c
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records

Bevilacqua, Fernando

Search in DiVA

By author/editor
Bevilacqua, Fernando
By organisation
School of InformaticsThe Informatics Research Centre
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 200 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 496 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf