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Conference Paper
Facial Landmark Localization Robust on the Eyes with Position Regression Network
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- Authors
- Chanwoong Kwak, Jaeyoon Jang, Hosub Yoon
- Issue Date
- 2020-06
- Citation
- International Conference on Ubiquitous Robots (UR) 2020, pp.130-133
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Facial landmark localization is essential for robot-human interaction. In particular, the human eye is more important because it can grasp a person's interests. However, the traditional method does not consider eye changes from the dataset, so the limitation is clear, this paper presents a data augmentation method for acquiring various eye images and a method for creating a robust eye landmark model with 2-stage training. Experiments on augmented 300W-LP datasets show that our method outperforms performance than the previous method.
- KSP Keywords
- Augmentation method, Data Augmentation, Facial landmark localization, Human eye, Traditional methods, robot and human interaction