Rendering of eyes for eye-shape registration and gaze estimation
Proceedings of the IEEE International Conference on Computer Vision
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Wood, E., Baltruaitis, T., Zhang, X., Sugano, Y., Robinson, P., & Bulling, A. (2015). Rendering of eyes for eye-shape registration and gaze estimation. Proceedings of the IEEE International Conference on Computer Vision, 2015 3756-3764. https://doi.org/10.1109/ICCV.2015.428
© 2015 IEEE. Images of the eye are key in several computer vision problems, such as shape registration and gaze estimation. Recent large-scale supervised methods for these problems require time-consuming data collection and manual annotation, which can be unreliable. We propose synthesizing perfectly labelled photo-realistic training data in a fraction of the time. We used computer graphics techniques to build a collection of dynamic eye-region models from head scan geometry. These were randomly posed to synthesize close-up eye images for a wide range of head poses, gaze directions, and illumination conditions. We used our model's controllability to verify the importance of realistic illumination and shape variations in eye-region training data. Finally, we demonstrate the benefits of our synthesized training data (SynthesEyes) by out-performing state-of-the-art methods for eye-shape registration as well as cross-dataset appearance-based gaze estimation in the wild.
Is supplemented by: https://doi.org/10.17863/CAM.57942
External DOI: https://doi.org/10.1109/ICCV.2015.428
This record's URL: https://www.repository.cam.ac.uk/handle/1810/284996