Adeia Guides Inc.

Kamal J Koshy

Dhananjay Lal

Reda Harb

Methods and systems are described for improved delivery of foveated rendering streams for media content delivery. Received video data is separated into a high acuity (HA) stream and a low acuity (LA) stream. The HA stream is marked to indicate HA transmission. A communication device that retransmits the HA stream based on the marking transmits the HA stream at a lower latency and a higher reliability than the LA stream. A receiving device receives the HA stream and the LA stream. A display device generates for display a combined stream including the HA stream and the LA stream. Artificial intelligence systems, including neural networks, are trained for improving the foveated rendering. Models are developed for the foveated rendering. Related apparatuses, devices, techniques, and articles are also described.

Delivery of foveated rendering streams for media content delivery

Authentication of a user wearing a head mounted display using wireless channel characteristics, such as wireless channel sounding, is disclosed. A transmission signal from a signal transmitter passes over the face or other parts of the head of the user and is received by a signal receiver, also in, at or near the head mounted display. The input signal received is processed according to the known transmission signal that was transmitted to obtain wireless channel characteristics. Based on these wireless channel characteristics a signal signature is identified, for example, using a machine learning based embedding technique. If the signal signature thus determined matches a signal signature previously associated with the user then the user is authenticated. User access to a resource or action may then be granted automatically.

User authentication based on wireless signal detection in a head mounted device

Methods and systems are provided herein for providing media asset recommendations to a user based on user input in real time and using a reinforcement learning model or media asset recommendation model. The model includes a plurality of states, each having a set of media asset recommendations, a plurality of available user input options, and a state value. During a browsing session, a first set of media asset recommendations is provided to a user based on a current state corresponding to the browsing session. The user then selects a user input option, and a second set of media asset recommendations is determined based on the received user input option. The second set of media asset recommendations is then provided to the user during the browsing session.

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Aurora, CO, United States of America

Kamal J Koshy