ALO: AI for Least Observed People

Detalhes bibliográficos
Autor(a) principal: Mamun, Shamim Al
Data de Publicação: 2021
Outros Autores: Daud, Mohammad Eusuf, Mahmud, Mufti, Kaiser, M. Shamim, Rossi, Andre Luis Debiaso [UNESP]
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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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
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