Duygu Algılamaya Dayalı Evrişimli Sinir Ağı ile Küçük Resmi Seçimi

Year 2021, Volume: 33 - ASYU 2020 Özel Sayısı, 88 - 93, 30.12.2021

Mahmut Çakar Kazım Yıldız , Önder Demir

https://doi.org/10.7240/jeps.900561

Cited By: 1

Abstract

Video yayın platformlarının kullanımı her geçen gün artmaktadır. Filmlerin ve dizilerin yayınlanması ve paylaşılması için platformlar geliştirme rekabeti artıyor. Bu platformların çoğaltılmasındaki amaç, kaliteyi arttırmak ve tek bir platform üzerinde takip etmektir. Film ve dizi platformları bu paylaşımlar için yapay zeka algoritmaları kullanır. Bu çalışmanın amacı, bir film veya diziden uygun kareler bularak kullanıcılar için daha çekici kapak fotoğrafları oluşturmaktır. Öncelikle platform üzerinde kapak / küçük resim haline getirilen çerçeveler elde edildi. Kapalı gözler, bulanık çerçeveler veya yüzsüz görüntülerden oluşan gereksiz çerçeveler kaldırıldı. Ayrıca derin öğrenme, görüntüleri yüzün kimliğine göre nesneler ve duygularla etiketlemek için kullanılır. En çok tekrar eden yüzlere sahip küçük resimler, her adımda bir yüz tanıma modeli geliştirilerek seçildi. Deneysel sonuçlar duygu modelinin başarılı olduğunu gösterdi.

Keywords

Emotion Detection, Convolutional Neural Network, Video Streaming Platforms, Thumbnail

Thumbnail Selection with Convolutional Neural Network Based on Emotion Detection

Abstract

The use of video broadcasting platforms is increasing day by day. The competition for developing platforms for the broadcasting and sharing of movies and TV series is increasing. The purpose of reproducing these platforms is to increase the quality and to trace them on a single platform. Film and TV series platforms use artificial intelligence algorithms for these shares. The aim of this study is to create more attractive cover photos for users by finding suitable frames from a movie or TV series. First, the frames that were transformed into covers/small pictures on the platform were obtained. Unnecessary frames which consist of closed eyes, blurry frames, or faceless images have been removed. Also, deep learning is used to label images with objects and emotions based on the identity of the face. The thumbnails with the most repeating faces were selected by developing a face recognition model at each step. The experimental results showed that the emotion model was successful.

Keywords

Emotion Detection, Video Streaming Platforms, Convolutional Neural Network, Thumbnail

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