Özni̇teli̇k bi̇rleşti̇rmeye dayali çok-di̇lde el alfabesi̇ tanima

Ahmet Alp Kindiroglu*, Hülya Yalçin, Lale Akarun

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

In this paper, we present a fingerspelling recognition module that has been designed to function in a smart system that is intended to act as a communication medium between people with hearing and visual disabilities. The method described is a computer vision based, close to real-time, automatic skin color based model hand gesture recognition module. We analyze and compare the recognition performance of appearance based hand descriptors on a self collected dataset. The dataset contains isolated videos of 88 different signs of the Czech, Turkish and Russian Sign Alphabets from 5 different signers with a total training and test length of 4 hours. On our test sets, we have achieved signer dependent and signer independent fingerspelling recognition rates of %82 and %42, respectively.

Tercüme edilen katkı başlığıFeature fusion based multilingual fingerspelling recognition
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011
Sayfalar214-217
Sayfa sayısı4
DOI'lar
Yayın durumuYayınlandı - 2011
Harici olarak yayınlandıEvet
Etkinlik2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 - Antalya, Turkey
Süre: 20 Nis 201122 Nis 2011

Yayın serisi

Adı2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011

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???event.eventtypes.event.conference???2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011
Ülke/BölgeTurkey
ŞehirAntalya
Periyot20/04/1122/04/11

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