Media Program Scene Detection Using Weighting Function

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Solution Overview

Problem

The challenge is to automatically determine optimal points for inserting advertisements into media programs without disrupting the user experience, as manual methods are subjective and time-consuming.

Innovation Solution

A method that analyzes media program characteristics to label similar parts and applies a weighting function to determine partitions, allowing for automated identification of optimal points for inserting information, such as advertisements, by comparing different partitionings of the media program.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual methods are used to determine advertisement insertion points, then subjective quality assessment is achieved, but time consumption and labor costs increase significantly

Engineering Contradiction:

Improvequality assessment accuracyVSAvoidreview time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical review process with an automated computer-based system that analyzes media programs using algorithms and weighting functions to objectively determine advertisement insertion points, eliminating the need for human reviewers while maintaining or improving assessment accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables the media program itself to provide the information needed for advertisement placement by automatically analyzing its own characteristics (scene changes, content structure) and generating insertion point recommendations without external human intervention

Inventive Principle:

Principle #25Self-service

2Productivity

If advertisements are inserted frequently to maximize revenue, then revenue generation increases, but user experience disruption increases

Engineering Contradiction:

Improverevenue generationVSAvoiduser experience disruption

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent applies different weighting factors to different locations within the media program based on local characteristics such as scene changes and content type, allowing advertisements to be placed in locations that are less disruptive to users while still maximizing overall revenue potential

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically adjusts the weighting parameters used to evaluate potential insertion points based on the specific characteristics of each media program and location, optimizing the balance between revenue generation and user experience for each unique case

Inventive Principle:

Principle #35Parameter changes

3Productivity

If automated analysis is used to determine advertisement insertion points, then productivity increases, but system complexity increases

Engineering Contradiction:

Improveprocessing speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent breaks down the complex task of determining advertisement insertion points into smaller, manageable components such as scene change detection, characteristic analysis, and weighting function evaluation, making the automated system more tractable and implementable

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces intermediate processing steps and data structures (such as weighted scoring mechanisms and partitioning algorithms) that mediate between raw media program data and final insertion point decisions, simplifying the overall decision-making process

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9336824B2Scene detection using weighting function

Publication Date: 2016.05.10 HULU LLC

AI summary

In one embodiment, a method includes analyzing characteristics of a media program to label parts of the media program with a plurality of labels where parts of the media program that are determined to be substantially similar are labeled with a same label. The method then analyzes different partitionings of a sequence of the labels to determine partitions for the media program based on a weighting function that is configured to weight the different partitionings based on portions created from the partitions in the different partitionings. Then, a partitioning for the media program is outputted based on comparing the different partitionings of the sequence of labels using the weighting function. The outputted partitioning partitions the media program into a set of portions and provides points for insertion of information for a service in the media program.