Apple Inc.

Rene Heideklang

Hua Gao

Tom Sengelaub

Hao Qin

A personalized eye model is used to generate synthetic gaze features at ground-truth eye poses G. Corresponding synthetic gaze poses Gare estimated from the synthetic gaze features using an average eye model. A linear regression is applied between Gand Gto generate a gaze correction function. The gaze correction function represents differences between the synthetic gaze Gof the subject eye at the display and that of the average eye model Gat the display, but does not contain security- or privacy-sensitive information. Further, the personalized eye model cannot be recovered from the gaze correction function, and thus the gaze correction function can be stored unencrypted and available for use during a cold boot of a device prior to login. On a cold boot of the device, the gaze correction function may be accessed and used with an average eye model to improve gaze-based interactions.

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Berlin, Germany

Rene Heideklang