| Autor: |
Thai, Chien, Nham, Ninh, Tran, Viet, Bui, Minh, Ninh, Huong, Tran, Hai |
| Zdroj: |
SN Computer Science; November 2023, Vol. 4 Issue: 6 |
| Abstrakt: |
In recent years, human head pose estimation has played a significant role in facial analysis with a variety of practical applications such as gaze estimation, virtual reality, driver assistance, etc. Due to its importance, in this paper, we propose a lightweight model to effectively deal with the task of head pose estimation. Firstly, the teacher models is trained on the synthesis dataset 300W-LPA to obtain the head pose pseudo labels; before an architecture with ResNet18 backbone is adopted and trained with the ensemble of these pseudo labels via the knowledge distillation process. Real-world head pose datasets AFLW-2000 and BIWI are used to evaluate our proposed approach efficacy. Experimental results prove the significant improvement of our proposed approach in the testing accuracy in comparison with other state-of-the-art head pose estimation methods. Furthermore, our model has the real-time speed of ∼300 FPS when inferring on Tesla V100. Source code and pre-trained weight are available at github.com/chientv99/headpose. |
| Databáze: |
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