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Yüz İfadesini Algılayarak Kullanıcının Ruh Haline Göre İçerik Öneren Mobil Uygulama

Yıl 2021, Sayı: 28, 192 - 197, 30.11.2021
https://doi.org/10.31590/ejosat.994802

Öz

Günümüzde insanlar, boş zamanlarını değerlendirmek için akıllı cihazları üzerinden dijital içerikler tüketmektedir. Ancak bazen kullanıcılar o anki ruh durumlarına göre bir film, dizi veya video izlemek ya da müzik dinlemek isteyebilir. Bu çalışmada, bu soruna çözüm olarak geliştirilen mobil uygulama anlatılmaktadır. Hedef cihaz olarak da hemen hemen herkesin sahip olduğu akıllı telefonlar seçilmiştir. Mobil uygulamada, kullanıcı rastgele olarak veya o anki ruh durumunu kendisi belirterek veya kullanıcının yüz ifadesine göre içerik önerileri alabilir. Yüz ifadesine göre içerik önerisinde bulunmak amacıyla, yapay zeka ve görüntü işleme kullanılarak, akıllı telefonun kamerasından kullanıcının anlık yüz ifadesi elde edilerek kullanıcının ruh hali tahmin edilir ve kullanıcıya bu ruh haline uygun dijital içerik önerilir. Ayrıca, hangi duyguya karşılık hangi içerik türünün içinden seçim yapılacağı, sistem yöneticisi tarafından belirlenebilir.

Destekleyen Kurum

Yok

Proje Numarası

Yok

Teşekkür

Yok

Kaynakça

  • A Good Movie to Watch. (2021). About - A Good Movie To Watch. Retrieved from https://agoodmovietowatch.com/about/
  • Amadeo, R. (2018). Google’s iron grip on Android: Controlling open source by any means necessary. Retrieved from https://arstechnica.com/gadgets/2018/07/googles-iron-grip-on-android-controlling-open-source-by-any-means-necessary/
  • Android. (2021a). Android Platform. Retrieved from https://developer.android.com/about
  • Android. (2021b). Application Fundamentals - Android Developers. Retrieved from https://developer.android.com/guide/components/fundamentals
  • Babanne, V., Borgaonkar, M., Katta, M., Kudale, P., & Deshpande, V. (2020). Emotion based personalized recommendation system. International Research Journal of Engineering and Technology (IRJET), 7(8), 701-705.
  • Charmy. (2021). Charmy. Retrieved from https://charmy.app/
  • Çümen, G. (2020). Görüntü İşleme Teknolojisi (Image Processing). Retrieved from https://medium.com/@gizemcumen85/g%C3%B6r%C3%BCnt%C3%BC-i%CC%87%C5%9Fleme-teknolojisi-image-processing-262bb58fbb27
  • Feelm. (2021). Feelm - Films for the way you feel. Retrieved from https://feelm.com/about
  • Flask. (2021). Foreword - Flask Documentation. Retrieved from https://flask.palletsprojects.com/en/2.0.x/foreword/
  • Flickseeker. (2021). Frequently Asked Questions - Flickseeker. Retrieved from https://flickseeker.com/faqs
  • Google Inc. (2021a). Cloud Computing Services. Retrieved from https://cloud.google.com/
  • Google Inc. (2021b). Cloud SQL. Retrieved from https://cloud.google.com/sql
  • Google Inc. (2021c). Why Google Cloud. Retrieved from https://cloud.google.com/why-google-cloud/
  • Mariappan, M. B., Suk, M., & Prabhakaran, B. (2012). FaceFetch: A User Emotion Driven Multimedia Content Recommendation System Based on Facial Expression Recognition. Paper presented at the 2012 IEEE International Symposium on Multimedia.
  • Metilda Florence, S., & Uma, M. (2020). Emotional Detection and Music Recommendation System based on User Facial Expression. IOP Conference Series: Materials Science and Engineering, 912.
  • Sharma, P. (2020). Multimedia Recommender System using Facial Expression Recognition. International Journal of Engineering Research & Technology (IJERT), 9(5), 674-676.
  • Shenk, J. (2021). FER. Retrieved from https://pypi.org/project/fer/
  • Statista. (2019). Share of global smartphone shipments by operating system from 2014 to 2023. Retrieved from https://www.statista.com/statistics/272307/market-share-forecast-for-smartphone-operating-systems/
  • TMDB. (2021). API Overview - The Movie Database. Retrieved from https://www.themoviedb.org/documentation/api

Mobile Application for Recommending Content Based on User’s Mood by Detecting Facial Expression

Yıl 2021, Sayı: 28, 192 - 197, 30.11.2021
https://doi.org/10.31590/ejosat.994802

Öz

Nowadays, people consume digital content on their smart devices to spend their free time. However, sometimes users might want to watch movies, TV series, videos or listen to music according to their current emotional state. In this paper, a mobile application is proposed as a solution to this problem. Since almost everyone owns a smartphone, smartphones have been determined as the target device. Via the mobile application, the users can receive content recommendations randomly or by entering their current mood or based on the user’s facial expression. In order to recommend content based on facial expression, the user’s mood is predicted by using artificial intelligence and image processing after the user’s instant facial expression is obtained from the smartphone’s camera, and digital content suitable for this mood is recommended to the user. In addition, the system administrator can determine which content type to choose against which emotion.

Proje Numarası

Yok

Kaynakça

  • A Good Movie to Watch. (2021). About - A Good Movie To Watch. Retrieved from https://agoodmovietowatch.com/about/
  • Amadeo, R. (2018). Google’s iron grip on Android: Controlling open source by any means necessary. Retrieved from https://arstechnica.com/gadgets/2018/07/googles-iron-grip-on-android-controlling-open-source-by-any-means-necessary/
  • Android. (2021a). Android Platform. Retrieved from https://developer.android.com/about
  • Android. (2021b). Application Fundamentals - Android Developers. Retrieved from https://developer.android.com/guide/components/fundamentals
  • Babanne, V., Borgaonkar, M., Katta, M., Kudale, P., & Deshpande, V. (2020). Emotion based personalized recommendation system. International Research Journal of Engineering and Technology (IRJET), 7(8), 701-705.
  • Charmy. (2021). Charmy. Retrieved from https://charmy.app/
  • Çümen, G. (2020). Görüntü İşleme Teknolojisi (Image Processing). Retrieved from https://medium.com/@gizemcumen85/g%C3%B6r%C3%BCnt%C3%BC-i%CC%87%C5%9Fleme-teknolojisi-image-processing-262bb58fbb27
  • Feelm. (2021). Feelm - Films for the way you feel. Retrieved from https://feelm.com/about
  • Flask. (2021). Foreword - Flask Documentation. Retrieved from https://flask.palletsprojects.com/en/2.0.x/foreword/
  • Flickseeker. (2021). Frequently Asked Questions - Flickseeker. Retrieved from https://flickseeker.com/faqs
  • Google Inc. (2021a). Cloud Computing Services. Retrieved from https://cloud.google.com/
  • Google Inc. (2021b). Cloud SQL. Retrieved from https://cloud.google.com/sql
  • Google Inc. (2021c). Why Google Cloud. Retrieved from https://cloud.google.com/why-google-cloud/
  • Mariappan, M. B., Suk, M., & Prabhakaran, B. (2012). FaceFetch: A User Emotion Driven Multimedia Content Recommendation System Based on Facial Expression Recognition. Paper presented at the 2012 IEEE International Symposium on Multimedia.
  • Metilda Florence, S., & Uma, M. (2020). Emotional Detection and Music Recommendation System based on User Facial Expression. IOP Conference Series: Materials Science and Engineering, 912.
  • Sharma, P. (2020). Multimedia Recommender System using Facial Expression Recognition. International Journal of Engineering Research & Technology (IJERT), 9(5), 674-676.
  • Shenk, J. (2021). FER. Retrieved from https://pypi.org/project/fer/
  • Statista. (2019). Share of global smartphone shipments by operating system from 2014 to 2023. Retrieved from https://www.statista.com/statistics/272307/market-share-forecast-for-smartphone-operating-systems/
  • TMDB. (2021). API Overview - The Movie Database. Retrieved from https://www.themoviedb.org/documentation/api
Toplam 19 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

İsmail Gündüz Bu kişi benim 0000-0003-4840-0612

Özgün Yılmaz 0000-0002-4394-4031

Proje Numarası Yok
Yayımlanma Tarihi 30 Kasım 2021
Yayımlandığı Sayı Yıl 2021 Sayı: 28

Kaynak Göster

APA Gündüz, İ., & Yılmaz, Ö. (2021). Yüz İfadesini Algılayarak Kullanıcının Ruh Haline Göre İçerik Öneren Mobil Uygulama. Avrupa Bilim Ve Teknoloji Dergisi(28), 192-197. https://doi.org/10.31590/ejosat.994802