Corpus ID: 49559000

Appearance-Based 3D Gaze Estimation with Personal Calibration

@article{Lindn2018AppearanceBased3G,
  title={Appearance-Based 3D Gaze Estimation with Personal Calibration},
  author={Erik Lind{\'e}n and Jonas Sj{\"o}strand and Alexandre Prouti{\`e}re},
  journal={ArXiv},
  year={2018},
  volume={abs/1807.00664}
}
  • Erik Lindén, Jonas Sjöstrand, Alexandre Proutière
  • Published in ArXiv 2018
  • Computer Science
  • We propose a way to incorporate personal calibration into a deep learning model for video-based gaze estimation. [...] Key Method To improve generalization, we predict gaze rays in 3D (origin and direction of gaze). In existing datasets, the 3D gaze is underdetermined, since all gaze targets are in the same plane as the camera. Experiments on synthetic data suggest it would be possible to learn accurate 3D gaze from only annotated gaze targets, without annotated eye positions.Expand Abstract

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    Citations

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    EyeNet: A Multi-Task Deep Network for Off-Axis Eye Gaze Estimation

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    Improving Few-Shot User-Specific Gaze Adaptation via Gaze Redirection Synthesis

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    Appearance-Based Gaze Estimation via Gaze Decomposition and Single Gaze Point Calibration

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    SalGaze: Personalizing Gaze Estimation using Visual Saliency

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