Immersive Content Feed Generation Using Semantic Mappings

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Solution Overview

Problem

The generation of content feeds for extended reality devices is often manual and subjective, leading to inconsistent results and inefficiencies, as it relies on human intuition and does not leverage immersive media effectively, resulting in non-immersive two-dimensional content.

Innovation Solution

An immersive content platform that automatically generates structured formats, semantic mappings, and electronic storyboards for extended reality devices, using natural language processing and machine learning to create immersive content feeds that are relevant and efficient, reducing human subjectivity and conserving computing resources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual content generation methods are used, then human intuition and subjectivity are applied, but the results are inconsistent and inefficient

Engineering Contradiction:

Improveconsistency of content generationVSAvoidefficiency of content generation

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system enables automated self-service content generation where the AI model automatically creates immersive content feeds from non-immersive input content without requiring manual human intervention for each content item, ensuring consistent application of transformation rules while maintaining high productivity

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual content creation process with an automated AI-based system that uses machine learning models to transform non-immersive content into immersive extended reality content feeds, eliminating human subjectivity while maintaining consistency and efficiency

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If non-immersive two-dimensional content is used, then simplicity is maintained, but user comprehension and engagement are reduced

Engineering Contradiction:

Improveuser comprehensionVSAvoidcontent format complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system transforms two-dimensional non-immersive content into three-dimensional immersive extended reality content feeds, adding spatial depth and immersion dimensions that enhance user comprehension and engagement while maintaining manageable complexity through automated generation processes

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Productivity

If automated content generation is implemented, then speed and efficiency are improved, but computing resource consumption increases

Engineering Contradiction:

Improvespeed of content generationVSAvoidcomputing resource utilization

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary automated generation of immersive content feeds from non-immersive content using AI models, preparing content in advance with optimized computing resource usage, and only processes content that meets relevancy thresholds, thereby improving speed while managing resource consumption efficiently

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10762678B2Representing an immersive content feed using extended reality based on relevancy

Publication Date: 2020.09.01 ACCENTURE GLOBAL SOLUTIONS LTD

AI summary

A device may generate, based on receiving feeder content, a structured format of the feeder content. The device may generate, based on the structured format of the feeder content, one or more semantic mappings for the feeder content. The device may generate, based on the one or more semantic mappings for the feeder content, an electronic storyboard of the feeder content. The device may generate an extended reality rendered content feed based on the electronic storyboard of the feeder content. The device may provide the extended reality rendered content feed to an extended reality device.