Deep Learning Approach to Face Pose Estimation for High-Speed Camera Network System
Seohyun Lee, Hyuno Kim, Masatoshi Ishikawa · 2020
Three-dimensional face pose estimation has been vastly researched in computer vision, as the face recognition techniques can be utilized in tremendous applications not only regarding human behavior monitoring but also about human-computer interaction. In this paper, we attempted to build a deep-learning model which classifies the pan angle of human head by directly applying convolutional neural network without preliminary image processing, for low-resolution face images. In comparison with the transfer learnings based on pre-trained model, customized simple model consisting of a few convolutional layers and dropout scheme showed an enhanced accuracy in face pan angle prediction.