# US 10,482,566 B2 · Personalized virtual reality content branch prediction

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- Number: US 10,482,566 B2
- Document ID: US10482566B2
- Status: Granted
- Kind: B2
- Application number: 15/937,425
- Filed: 2018-03-27
- Published: 2018-10-04
- Granted: 2019-11-19
- Earliest claimed: 2017-03-31
- Assignees: Intel Corporation
- Applicants: Intel Corporation
- Inventors: Rajesh Poornachandran; Niveditha Sundaram; Ryan D. Saffores; Kalyan K. Kaipa; Gomathi Ramamurthy
- Web page: https://patentgrep.com/patent/US10482566B2

## CPC

- G06T 1/20: Processor architectures; Processor configuration, e.g. pipelining
- G06F 3/011: {Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00)}
- G06F 3/012: {Head tracking input arrangements}
- G06N 5/025: Extracting rules from data
- G06N 20/20: Ensemble learning
- G06Q 30/0269: {based on user profile or attribute}
- H04L 67/131: Protocols for games, networked simulations or virtual reality
- H04L 67/306: User profiles
- H04L 67/34: {involving the movement of software or configuration parameters (network booting or remote initial program loading [RIPL] G06F9/4416)}
- G06F 2203/011: Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns
- G06N 5/02: Knowledge representation; Symbolic representation
- G06N 5/04: Inference or reasoning models
- G06Q 30/0271: {Personalized advertisement}
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

Methods, apparatus, and machine-readable mediums are described for doing predictive content branch selection for rendering environments such as virtual reality systems. User data is aggregated from multiple users. Each user is classified based upon the user data. Personalization parameters are identified for each of the plurality of users. Content to be presented is determined and modified with a modification for a user based upon the personalization parameters for the user. The modified content is sent to the user.

## Claims

### Claim 1

A system for content branch selection, the system comprising:
processing circuitry to:
aggregate user data and content data from a plurality of users, the user data and content data provided from a plurality of devices, the user data collected while the content data is displayed by the plurality of devices, and the user data comprising one of: a breathing pattern, heart rate, brainwave pattern, eye dilation, eye movement, geo fence data, ambient lighting data, user motion, facial recognition, facial expression, user agility, hand-eye coordination data, key words, and audio cues;
classify a physical state with a response classifier for each of the plurality of users based on the user data and the content data, wherein the response classifier is trained using the user data and content data;
identify personalization parameters for each of the plurality of users;
identify content to present to the plurality of users, including a first user and a second user; determine, using the response classifier, a first amount of user movement and a first rate of changes of the identified content for the first user based on a physical state of the first user and the identified content;
modify the identified content with a first modification based on the first amount of user movement and the first rate of changes of the identified content for the first user and personalization parameters for the first user;
determine, using the response classifier, a second amount of user movement and a second rate of changes of the identified content for the second user based on a physical state of the second user and the identified content;
modify the identified content with a second, different, modification based on the second amount of user movement and the second rate of changes of the identified content for the second user and personalization parameters for the second user;
send the identified content with the first modification to the first user; and send the identified content with the second modification to the second user.

### Claim 2 (depends on 1)

The system of claim 1, the identified content with the first modification is presented to the first user in in one of a virtual reality, augmented reality, mixed reality environment.

### Claim 3 (depends on 2)

The system of claim 2, wherein the processing circuitry is to update the user data based upon additional user data received from the first user based upon the identified content with the first modification being presented to the first user.

### Claim 4 (depends on 1)

The system of claim 1, further comprising a trusted execution environment to synchronize time with the plurality of devices, wherein the processing circuitry is to relate the received user data with a frame from the content data.

### Claim 5 (depends on 1)

The system of claim 1, where to classify each of the plurality of users the processing circuitry is to determine an emotional state of a user for the content data.

### Claim 6 (depends on 1)

The system of claim 1, where to identify personalization parameters the processing circuitry is to determine an enjoyment level of the content data.

### Claim 7 (depends on 1)

The system of claim 1, where to modify the identified content with the first modification for the first user the processing circuitry is to determine an insertion location for a content event.

### Claim 8 (depends on 7)

The system of claim 7, where the processing circuitry is to determine an effectiveness of the content event.

### Claim 9 (depends on 8)

The system of claim 8, where the processing circuitry is to determine a second insertion location for the content event based upon the effectiveness of the content event.

### Claim 10 (depends on 1)

The system of claim 1, where the processing circuitry is to determine a level of motion sickness in the first user based upon the user data, where the first modification is based upon the level of motion sickness.

### Claim 11 (depends on 1)

The system of claim 1, where to modify the identified content with a first modification the processing circuitry is to determine an angle of head movement based on the identified content and the aggregated user data, the modification is based upon the angle of head movement.

### Claim 12 (depends on 11)

The system of claim 11, where the processing circuitry is to:
determine an error amount from the angle of head movement;
create additional content based upon the error amount; and
send the additional content to the first user.

### Claim 13

A method for content branch selection, the method comprising:
receiving user data and content data from a plurality of users, the user data and content data provided from a plurality of devices, the user data collected while the content data is displayed by the plurality of devices, and the user data comprising one of: a breathing pattern, heart rate, brainwave pattern, eye dilation, eye movement, geo fence data, ambient lighting data, user motion, facial recognition, facial expression, user agility, hand-eye coordination data, key words, and audio cues;
classifying a physical state with a response classifier for each of the plurality of users based on the user data and the content data, wherein the response classifier is trained using the user data and content data;
identifying personalization parameters for each of the plurality of users;
identifying content to present to the plurality of users, including a first user and a second user; determining, using the response classifier, a first amount of user movement and a first rate of changes of the identified content for the first user based on a physical state of the first user and the identified content;
modifying the identified content with a first modification based on the first amount of user movement and the first rate of changes of the identified content for the first user and personalization parameters for the first user;
determining, using the response classifier, a second amount of user movement and a second rate of changes of the identified content for the second user based on a physical state of the second user and the identified content;
modifying the identified content with a second, different, modification based on the second amount of user movement and the second rate of changes of the identified content for the second user and personalization parameters for the second user;
sending the identified content with the first modification to the first user; and sending the identified content with the second modification to the second user.

### Claim 14 (depends on 13)

The method of claim 13, the identified content with the first modification is presented to the first user in one of a virtual reality, augmented reality, mixed reality environment.

### Claim 15 (depends on 14)

The method of claim 14, further comprising updating the user data based upon additional user data received from the first user based upon the identified content with the first modification being presented to the first user.

### Claim 16

At least one non-transitory computer-readable medium, including instructions, which when executed by a machine, cause the machine to perform operations:
receiving user data and content data from a plurality of users, the user data and content data provided from a plurality of devices, the user data collected while the content data is displayed by the plurality of devices, and the user data comprising one of: a breathing pattern, heart rate, brainwave pattern, eye dilation, eye movement, geo fence data, ambient lighting data, user motion, facial recognition, facial expression, user agility, hand-eye coordination data, key words, and audio cues;
classifying a physical state with a response classifier for each of the plurality of users based on the user data and the content data, wherein the response classifier is trained using the user data and content data;
identifying personalization parameters for each of the plurality of users;
identifying content to present to the plurality of users, including a first user and a second user; determining, using the response classifier, a first amount of user movement and a first rate of changes of the identified content for the first user based on a physical state of the first user and the identified content;
modifying the identified content with a first modification based on the first amount of user movement and the first rate of changes of the identified content for the first user and personalization parameters for the first user;
determining, using the response classifier, a second amount of user movement and a second rate of changes of the identified content for the second user based on a physical state of the second user and the identified content;
modifying the identified content with a second, different, modification based on the second amount of user movement and the second rate of changes of the identified content for the second user and personalization parameters for the second user;
sending the identified content with the first modification to the first user; and sending the identified content with the second modification to the second user.

### Claim 17 (depends on 16)

The at least one non-transitory computer-readable medium of claim 16, the identified content with the first modification is presented to the first user in one of a virtual reality, augmented reality, mixed reality environment.

### Claim 18 (depends on 17)

The at least one non-transitory computer-readable medium of claim 17, where the operations further comprise updating the user data based upon additional user data received from the first user based upon the identified content with the first modification being presented to the first user.

### Claim 19 (depends on 16)

The at least one non-transitory computer-readable medium of claim 16, where the operations further comprise:
synchronizing time with the plurality of devices; and
relating the received user data with a frame from the content data.

### Claim 20

An apparatus for content branch selection, the apparatus comprising:
means for receiving user data and content data from a plurality of users, the user data and content data provided from a plurality of devices, the user data collected while the content data is displayed by the plurality of devices, and the user data comprising one of: a breathing pattern, heart rate, brainwave pattern, eye dilation, eye movement, geo fence data, ambient lighting data, user motion, facial recognition, facial expression, user agility, hand-eye coordination data, key words, and audio cues;
means for classifying a physical state with a response classifier for each of the plurality of users based on the user data and the content data, wherein the response classifier is trained using the user data and content data;
means for identifying personalization parameters for each of the plurality of users;
means for identifying content to present to the plurality of users, including a first user and a second user;
means for determining, using the response classifier, a first amount of user movement and a first rate of changes of the identified content for the first user based on a physical state of the first user and the identified content;
means for modifying the identified content with a first modification based on the first amount of user movement and the first rate of changes of the identified content for the first user and personalization parameters for the first user;
means for determining, using the response classifier, a second amount of user movement and a second rate of changes of the identified content for the second user based on a physical state of the second user and the identified content;
means for modifying the identified content with a second, different, modification based on the second amount of user movement and the second rate of changes of the identified content for the second user and personalization parameters for the second user;
means for sending the identified content with the first modification to the first user; and means for sending the identified content with the second modification to the second user.

### Claim 21 (depends on 20)

The apparatus of claim 20, the identified content with the first modification is presented to the first user in one of a virtual reality, augmented reality, mixed reality environment.