Animated Background Personalization for Contextual Media Content

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Solution Overview

Problem

Existing media content, particularly interstitial advertisements, lack user context and are often perceived as intrusive due to irrelevant content, leading to a negative user experience.

Innovation Solution

A system dynamically generates an animated background for media content based on contextual data from the content and user profile, using machine learning techniques to personalize the background and enhance user engagement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If media content is displayed without contextual personalization, then the delivery process is simple and fast, but the user experience is negative and engagement is low

Engineering Contradiction:

Improveuser experienceVSAvoidcontent generation system

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system dynamically generates animated backgrounds based on real-time contextual data from user profiles and media content, transforming static advertisements into adaptive, personalized experiences that respond to user characteristics and content type

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system modifies visual parameters of the background (colors, patterns, animations) based on contextual parameters extracted from user profiles and media content, creating personalized experiences through parameter transformation

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If static backgrounds are used for media content, then the production process is simple, but the relevance and engagement of advertisements are reduced

Engineering Contradiction:

Improverelevance of advertisementsVSAvoidbackground generation process

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system pre-processes user profile data and media content metadata to extract contextual information before generating the animated background, enabling personalized content creation through advance preparation of contextual parameters

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically extracts contextual data from user profiles and media content without requiring manual input or human editing, enabling self-service personalization through automated context analysis

Inventive Principle:

Principle #25Self-service

3Productivity

If human editing is used to personalize media content, then the quality of customization is high, but the time consumption and production cost increase

Engineering Contradiction:

Improveproduction efficiencyVSAvoidcustomization quality

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The system replaces manual human editing with automated machine learning models that generate personalized animated backgrounds through algorithmic processing of contextual data, substituting mechanical manual labor with automated computational processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260075293A1Customization of media content with an animated background

Publication Date: 2026.03.12 ROKU INC

AI summary

Aspects of the disclosed technology provide solutions for dynamically generating media content with an animated background based on contextual data. An example method can include receiving first content. Additionally, the method can include generating an animated background including one or more items associated with the first content based on context information associated with the first content. Moreover, the method can include, placing the media content within the animated background. Systems and machine-readable media are also provided.