Video Intro Segment Matching Using Hard and Soft Fingerprints

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Solution Overview

Problem

Identifying the introduction portion of a video program, such as a television series, is challenging due to variations in directors, actors, guest hosts, and inconsistent compression artifacts across episodes, making manual identification time-consuming and computationally intense.

Innovation Solution

A machine-learning model, such as a gradient boosting regressor, is used to identify hard- and soft-matching video segments by analyzing video fingerprints and lengths, automatically determining the introduction portion by dilating hard-matching pairs with soft-matching segments, reducing the need for manual labeling.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual identification of introduction portions is performed, then identification accuracy can be maintained, but time consumption and computational resources increase significantly

Engineering Contradiction:

Improveidentification accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary action by extracting and storing introduction portions from reference episodes before they are needed for comparison. Video fingerprints are pre-computed and stored in a database, allowing rapid comparison during target episode analysis without performing the full identification process in real-time

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates a copy of the introduction portion from reference video content and stores it as reference data. This copied reference introduction is then compared against target episodes using video fingerprinting, eliminating the need for manual identification in each target episode while maintaining consistent accuracy standards

Inventive Principle:

Principle #26Copying

2Reliability

If traditional video analysis methods are used to identify introduction portions, then comprehensive analysis can be performed, but computational complexity and processing time increase

Engineering Contradiction:

Improveidentification reliabilityVSAvoidcomputational complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The video content is segmented into discrete portions with clear boundaries - specifically separating the introduction portion from the main content. Video fingerprinting divides the video into frames and extracts key features, creating segmented representations that are computationally efficient to compare while maintaining reliable identification of the introduction segment boundaries

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Video fingerprinting serves as an intermediary technique between the raw video content and the identification decision. Instead of directly analyzing complex video sequences, the system converts video content into fingerprint representations that capture essential characteristics while reducing computational complexity for comparison operations

Inventive Principle:

Principle #24Intermediary (Mediator)

3Quantity of substance

If video compression techniques are applied to reduce file size, then storage and transmission efficiency improve, but compression artifacts create variations that complicate identification

Engineering Contradiction:

Improvedata sizeVSAvoidvideo segment matching precision

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system changes parameters by using video fingerprinting that is robust to compression artifacts. Instead of relying on exact pixel-level matching, the fingerprinting technique extracts stable features that remain consistent despite compression variations, allowing precise identification even when compression parameters differ between episodes

Inventive Principle:

Principle #35Parameter changes

4Adaptability or versatility

If introduction portions are identified in each episode individually, then episode-specific variations can be detected, but processing time and resources multiply across the entire series

Engineering Contradiction:

Improveepisode-specific adaptationVSAvoidprocessing throughput

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system achieves universality by creating a single reference introduction that can be applied across multiple episodes. The reference introduction portion is extracted once and then used to identify introductions in numerous target episodes, serving multiple functions simultaneously and dramatically improving processing throughput while still adapting to episode-specific variations through the comparison process

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250342700A1Systems, methods, and devices for determining an introduction portion in a video program

Publication Date: 2025.11.06 COMCAST CABLE COMM LLC

AI summary

Systems, methods, and devices relating to determining an introduction portion in a video program are described herein. A method may determine first and second hard-matching pairs of video segments in first and second video content such that video fingerprints of the first hard-matching pair match and video fingerprints of the second hard-matching pair also match. The method may classify a third pair of video segments in the first and second video content, sequentially between the first and second hard-matching pairs, as a soft-matching pair of video segments of an introduction portion. The method may use the classification of the third pair of video segments as a soft-matching pair to determine a model configured to determine that a pair of video segments in two video content items are a soft-matching pair of video segments of an introduction portion.