ALO: AI for Least Observed People
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/978-3-030-82269-9_24 http://hdl.handle.net/11449/222288 |
Resumo: | In recent years, visual assistants of humans are taking place in the consumer market–the eye-line of humans equipped with a see-through optical display. Computer Vision Technology may play a vital role in visually challenged people to carry out their daily activities without much dependency on others. In this paper, we introduce ALO (AI for Least Observed) as an assistive glass for blind people. It can listen as a companion, read from the internet on the fly, detect surrounding objects and obstacles for freedom of movement, and recognize the faces he is communicating with. This glass can be a virtual companion of the users for social safety from unknown people, reduce the dependency of others. This system uses the camera for identifying human faces using MTCNN deep learning technique, bone conduction microphone, and google API (Application Programming Interface) for translating voice to text and text to bone conduction sound. A Market Valuable Product (MVP) has already been developed depending on our survey of over 300 visually impaired persons in Europe and Asia. |
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Repositório Institucional da UNESP |
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2946 |
spelling |
ALO: AI for Least Observed PeopleBlind visionFace recognitionObject detectionSmart glassIn recent years, visual assistants of humans are taking place in the consumer market–the eye-line of humans equipped with a see-through optical display. Computer Vision Technology may play a vital role in visually challenged people to carry out their daily activities without much dependency on others. In this paper, we introduce ALO (AI for Least Observed) as an assistive glass for blind people. It can listen as a companion, read from the internet on the fly, detect surrounding objects and obstacles for freedom of movement, and recognize the faces he is communicating with. This glass can be a virtual companion of the users for social safety from unknown people, reduce the dependency of others. This system uses the camera for identifying human faces using MTCNN deep learning technique, bone conduction microphone, and google API (Application Programming Interface) for translating voice to text and text to bone conduction sound. A Market Valuable Product (MVP) has already been developed depending on our survey of over 300 visually impaired persons in Europe and Asia.Institute of Information Technology Jahangirngar UniversityConsultant Ministry of financeUniversity of NottinghamUniversidade Estadual PaulistaUniversidade Estadual PaulistaJahangirngar UniversityMinistry of financeUniversity of NottinghamUniversidade Estadual Paulista (UNESP)Mamun, Shamim AlDaud, Mohammad EusufMahmud, MuftiKaiser, M. ShamimRossi, Andre Luis Debiaso [UNESP]2022-04-28T19:43:43Z2022-04-28T19:43:43Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject306-317http://dx.doi.org/10.1007/978-3-030-82269-9_24Communications in Computer and Information Science, v. 1435, p. 306-317.1865-09371865-0929http://hdl.handle.net/11449/22228810.1007/978-3-030-82269-9_242-s2.0-85113575810Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCommunications in Computer and Information Scienceinfo:eu-repo/semantics/openAccess2022-04-28T19:43:43Zoai:repositorio.unesp.br:11449/222288Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:04:47.182412Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
ALO: AI for Least Observed People |
title |
ALO: AI for Least Observed People |
spellingShingle |
ALO: AI for Least Observed People Mamun, Shamim Al Blind vision Face recognition Object detection Smart glass |
title_short |
ALO: AI for Least Observed People |
title_full |
ALO: AI for Least Observed People |
title_fullStr |
ALO: AI for Least Observed People |
title_full_unstemmed |
ALO: AI for Least Observed People |
title_sort |
ALO: AI for Least Observed People |
author |
Mamun, Shamim Al |
author_facet |
Mamun, Shamim Al Daud, Mohammad Eusuf Mahmud, Mufti Kaiser, M. Shamim Rossi, Andre Luis Debiaso [UNESP] |
author_role |
author |
author2 |
Daud, Mohammad Eusuf Mahmud, Mufti Kaiser, M. Shamim Rossi, Andre Luis Debiaso [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Jahangirngar University Ministry of finance University of Nottingham Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Mamun, Shamim Al Daud, Mohammad Eusuf Mahmud, Mufti Kaiser, M. Shamim Rossi, Andre Luis Debiaso [UNESP] |
dc.subject.por.fl_str_mv |
Blind vision Face recognition Object detection Smart glass |
topic |
Blind vision Face recognition Object detection Smart glass |
description |
In recent years, visual assistants of humans are taking place in the consumer market–the eye-line of humans equipped with a see-through optical display. Computer Vision Technology may play a vital role in visually challenged people to carry out their daily activities without much dependency on others. In this paper, we introduce ALO (AI for Least Observed) as an assistive glass for blind people. It can listen as a companion, read from the internet on the fly, detect surrounding objects and obstacles for freedom of movement, and recognize the faces he is communicating with. This glass can be a virtual companion of the users for social safety from unknown people, reduce the dependency of others. This system uses the camera for identifying human faces using MTCNN deep learning technique, bone conduction microphone, and google API (Application Programming Interface) for translating voice to text and text to bone conduction sound. A Market Valuable Product (MVP) has already been developed depending on our survey of over 300 visually impaired persons in Europe and Asia. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 2022-04-28T19:43:43Z 2022-04-28T19:43:43Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/978-3-030-82269-9_24 Communications in Computer and Information Science, v. 1435, p. 306-317. 1865-0937 1865-0929 http://hdl.handle.net/11449/222288 10.1007/978-3-030-82269-9_24 2-s2.0-85113575810 |
url |
http://dx.doi.org/10.1007/978-3-030-82269-9_24 http://hdl.handle.net/11449/222288 |
identifier_str_mv |
Communications in Computer and Information Science, v. 1435, p. 306-317. 1865-0937 1865-0929 10.1007/978-3-030-82269-9_24 2-s2.0-85113575810 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Communications in Computer and Information Science |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
306-317 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129390267072512 |