Media Stream Scene Detection for Optimal Supplemental Placement

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Solution Overview

Problem

Existing approaches for inserting supplemental content into a media stream fail to consider the varying motivations of users at different points in time and the unique characteristics of individual users, leading to suboptimal placement of supplemental content.

Innovation Solution

The system performs automated content recognition (ACR) to identify scene changes in a media stream, identifies potential supplemental content spots based on these changes, and conducts multivariate testing across multiple media devices to determine the optimal spot for inserting supplemental content.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If supplemental content is inserted at fixed predetermined spots in a media stream, then the insertion process is simple and consistent, but user engagement and consumption of supplemental content is suboptimal because it does not account for varying user motivations at different points in the media stream

Engineering Contradiction:

Improvesupplemental content consumptionVSAvoidcontent insertion system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis of the media stream to identify scene changes and potential supplemental content spots before actual insertion. ACR technology analyzes video frames, audio tracks, and metadata in advance to determine optimal insertion points based on scene transitions, cliffhanger detection, and user engagement patterns, thereby resolving the contradiction between simple insertion and optimal engagement

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts supplemental content insertion points based on real-time analysis of user characteristics, viewing context, and scene progression. Rather than using fixed predetermined spots, the system adapts insertion timing to match user motivation levels, scene importance, and individual user preferences, thereby maximizing consumption while managing complexity through automated dynamic decision-making

Inventive Principle:

Principle #15Dynamics

2Productivity

If supplemental content is inserted manually at appropriate points, then placement can be optimized for user engagement, but the process is time intensive and error prone

Engineering Contradiction:

Improvesupplemental content consumptionVSAvoidcontent insertion time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs self-service by automatically analyzing the media stream, identifying scene changes, and determining optimal supplemental content insertion points without human intervention. ACR technology autonomously processes video and audio data to detect scene transitions and cliffhangers, then automatically selects insertion spots that maximize user engagement, eliminating the time-intensive and error-prone manual insertion process while maintaining high engagement levels

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process of identifying and inserting supplemental content with an automated electronic system using ACR technology. The system substitutes human analysts and manual insertion operations with algorithmic scene change detection, automated optimal spot identification, and programmatic content insertion, thereby dramatically reducing time consumption and eliminating human error while maintaining or improving engagement optimization

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If existing approaches insert supplemental content without considering user characteristics, then the insertion process is straightforward, but it fails to maximize consumption because it ignores unique user motivations and viewing contexts

Engineering Contradiction:

Improvesupplemental content consumptionVSAvoiduser-specific content optimization

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system applies local quality by tailoring supplemental content insertion to specific user characteristics, viewing contexts, and scene conditions rather than using a uniform approach. ACR technology analyzes individual user profiles, viewing history, and current media context to determine optimal insertion points for each user, thereby maximizing consumption through personalized adaptation while maintaining system manageability through automated segmentation and targeting

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS12348795B2Automatically determining an optimal supplemental content spot in a media stream

Publication Date: 2025.07.01 ROKU INC

AI summary

Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for determining an optimal spot to insert supplemental content into a media stream to maximize the consumption of the supplemental content by users. An example embodiment operates by performing automated content recognition (ACR) on the media stream, thereby determining scene changes in the media stream. The embodiment identifies a plurality of potential supplemental content spots in the media stream based on the determined scene changes. The embodiment then performs a multivariate test involving test supplemental content over a portion of the potential supplemental content spots to a plurality of media devices, thereby determining the optimal supplemental content spot among the plurality of potential supplemental content spots in the media stream.