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AssigneeL'oreal
InventorsAlex Levinshtein, Edmund Phung, Parham Aarabi
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This document relates to hybrid eye center localization using machine learning, namely cascaded regression and hand-crafted model fitting to improve a computer. There are proposed systems and methods of eye center (iris) detection using a cascade regressor (cascade of regression forests) as well as systems and methods for training a cascaded regressor. For detection, the eyes are detected using a facial feature alignment method. The robustness of localization is improved by using both advanced features and powerful regression machinery. Localization is made more accurate by adding a robust circle fitting post-processing step. Finally, using a simple hand-crafted method for eye center localization, there is provided a method to train the cascaded regressor without the need for manually annotated training data. Evaluation of the approach shows that it achieves state-of-the-art performance.
A device comprising a processing unit coupled to a storage device storing instructions, which instructions, when executed by the processing unit, configure the device to provide components to determine eye center localization in an image source, the components comprising:
A computer implemented method to determine eye center localization in an image source, the method executed by a processing unit of a computing device and comprising:
A method to simulate reality comprising:
Dependencies are inferred from the claim text.