Sony Interactive Entertainment Inc. (20240207731). DYNAMIC ENCODING PARAMETERS FOR LOW LATENCY STREAMING simplified abstract

DYNAMIC ENCODING PARAMETERS FOR LOW LATENCY STREAMING

Organization Name

Sony Interactive Entertainment Inc.

Inventor(s)

Eric Chen of Saratoga CA (US)

DYNAMIC ENCODING PARAMETERS FOR LOW LATENCY STREAMING - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240207731 titled 'DYNAMIC ENCODING PARAMETERS FOR LOW LATENCY STREAMING

The abstract describes a method implemented in a cloud gaming system that involves executing a game session of a video game, using a machine learning model to determine encoding parameter settings based on game state data, applying these settings to generate compressed gameplay video, and streaming it to a client device.

• The method involves executing a game session of a video game.
• A machine learning model is used to determine encoding parameter settings based on game state data.
• An encoder applies the encoding parameter settings to generate compressed gameplay video.
• The compressed gameplay video is streamed over a network to a client device.

Potential Applications: - Cloud gaming platforms - Video game streaming services - Remote gaming solutions

Problems Solved: - Efficient encoding of gameplay video - Reduced network bandwidth usage - Improved streaming quality for gaming

Benefits: - Enhanced gaming experience for users - Lower latency in gameplay streaming - Cost-effective video compression techniques

Commercial Applications: Cloud gaming services can utilize this method to offer high-quality gameplay streaming to users, potentially increasing their user base and revenue streams.

Questions about the technology: 1. How does the machine learning model determine encoding parameter settings? 2. What are the advantages of using compressed gameplay video in cloud gaming systems?

Original Abstract Submitted

a method implemented in a cloud gaming system having at least one server computer is provided, including the following operations: executing a game session of a video game, wherein the execution of the game session renders gameplay video and generates game state data; using a machine learning (ml) model to determine encoding parameter settings based on the game state data; applying, by an encoder, the encoding parameter settings for processing of the gameplay video to generate compressed gameplay video; streaming the compressed gameplay video over a network to a client device.