Magic Leap, Inc.

Joelle Zimmermann

Andrew Rabinovich

Vijay Badrinarayanan

Thomas Marshall Miller, Iv

John Monos

Srivignesh Rajendran

Tarrence Van As

Zhengyang Wu

Techniques related to the computation of gaze vectors of users of wearable devices are disclosed. A neural network may be trained through first and second training steps. The neural network may include a set of feature encoding layers and a plurality of sets of task-specific layers that each operate on an output of the set of feature encoding layers. During the first training step, a first image of a first eye may be provided to the neural network, eye segmentation data may be generated using the neural network, and the set of feature encoding layers may be trained. During the second training step, a second image of a second eye may be provided to the neural network, network output data may be generated using the neural network, and the plurality of sets of task-specific layers may be trained.

Eye tracking and gaze estimation using off-axis camera

Examples of systems and methods for rendering an avatar in a mixed reality environment are disclosed. The systems and methods may be configured to automatically select avatar characteristics that optimize gaze perception by the user, based on context parameters associated with the virtual environment.

Avatar customization for optimal gaze discrimination

Growing community of inventors

Los Angeles, CA, United States of America

Joelle Zimmermann