논문 해외 국제전문학술지(SCI급) Head pose-free gaze estimation using domain adaptation
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2021-08
- 저자명 Ahn, B (Ahn, Byungtae),Seo, M (Seo, Minseok),최동걸
- 학술지명 ELECTRONICS LETTERS
- 발행처명 WILEY
- 발행국가 해외
- 논문언어 외국어
- 전체저자수 3
홈페이지논문 초록 (Abstract)
Human gaze information has been widely used in various areas, such as medical diagnosis and human-computer interactions (HCI). This study proposes a head pose-free 3D gaze estimation method using a deep convolutional neural network (DCNN). To infer gaze direction, only a small grayscale image is required without any special devices such as an infrared (IR) illuminator and RGBD sensor. A domain adaptation method to reduce the feature gap between real and synthetic image data is also proposed here. Moreover, a novel synthetic dataset (SynFace) that contains head poses, gaze directions, and facial landmarks is established and released. The proposed method outperforms state-of-the-art methods and achieves a mean error of less than 4(White circle).