Gaze Estimation by Attention Using a Two-Stream Regression Network
31st IEEE Conference on Signal Processing and Communications Applications (SIU), İstanbul, Türkiye, 5 - 08 Temmuz 2023, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/siu59756.2023.10223906
- Basıldığı Şehir: İstanbul
- Basıldığı Ülke: Türkiye
- Anahtar Kelimeler: gaze estimation, attention mechanism, human-computer interaction
- Eskişehir Osmangazi Üniversitesi Adresli: Evet
Özet
Determining the point of view of people is an important human-computer interaction problem that has been studied for a long time. This subject, which has many applications, is used in different fields such as marketing, automotive, medical, games and entertainment. In this study, we propose a remote eye tracking method that makes gaze estimation using convolutional neural network based on regression. The proposed method uses a two-stream deep learning architecture that utilizes eye images and iris segmentation masks obtained through segmentation neural network. The architecture employed selective attention-based mechanisms to enhance its performance. Experimental results demonstrate that the attention-based two-stream architecture outperforms both single-stream deep learning architectures and architectures without attention mechanisms.