Video Fingerprint Matching for Duplicate Detection

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Solution Overview

Problem

Managing large video libraries is challenging due to the difficulty in identifying and organizing duplicate video content, leading to inefficient storage and user navigation issues, as well as the need for expensive manual identification and processing of unauthorized videos.

Innovation Solution

A system and method that detects duplicate video content by generating video fingerprints, comparing them to a reference set, and classifying segments as matching or non-matching, using techniques such as location-sensitive hashing and dynamic time warping to identify and eliminate duplicates.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual identification of video content is used, then identification accuracy is improved, but cost and time consumption increase significantly

Engineering Contradiction:

Improveidentification accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables self-service by automatically generating video fingerprints and comparing them against a reference database without human intervention. The automated fingerprinting process extracts visual features, generates compact representations, and performs matching operations to identify duplicate videos, eliminating the need for manual identification while maintaining accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual identification process with an automated computational system. Video fingerprints serve as digital representations that can be automatically processed, stored, and compared using computer algorithms, substituting human analysts with automated fingerprint generation and matching mechanisms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If multiple copies of the same video content are stored, then content availability is improved, but storage space is wasted

Engineering Contradiction:

Improvecontent availabilityVSAvoidstorage space

Core Design Contradiction:

Adaptability or versatilityVSVolume of stationary object

Solution Approach 1:

The system implements feedback by continuously comparing new video uploads against the reference database using fingerprint matching. When duplicates are detected, the system provides feedback to identify and remove redundant copies, enabling the storage system to maintain content availability while eliminating duplicate storage waste through automated detection and classification.

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If a large number of video files are stored, then content diversity is improved, but organization and searchability deteriorate

Engineering Contradiction:

Improvecontent diversityVSAvoidsearchability

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The patent applies segmentation by dividing each video into temporal segments and generating fingerprints for each segment. This segmentation allows the system to organize and index video content at the segment level, improving searchability by enabling users to search for specific scenes or moments rather than requiring search across entire videos, while maintaining content diversity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system transforms video content into parameter-based fingerprints that capture visual characteristics. By converting videos into compact fingerprint representations with specific parameters (visual features, temporal information), the system improves organization and searchability while preserving content diversity through accurate fingerprint-based indexing and retrieval.

Inventive Principle:

Principle #35Parameter changes

4Productivity

If automated video matching is implemented, then processing speed is improved, but matching accuracy may be affected by video quality variations

Engineering Contradiction:

Improveprocessing speedVSAvoidmatching accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system implements dynamics by adapting the fingerprint matching process to handle video quality variations. The fingerprint generation and comparison algorithms are designed to be robust to changes in video quality, dynamically adjusting to different conditions while maintaining both speed and accuracy in detecting duplicate content.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS8238669B2Detection and classification of matches between time-based media

Publication Date: 2012.08.07 GOOGLE LLC

AI summary

A system and method detects matches between portions of video content. A matching module receives an input video fingerprint representing an input video and a set of reference fingerprints representing reference videos in a reference database. The matching module compares the reference fingerprints and input fingerprints to generate a list of candidate segments from the reference video set. Each candidate segment comprises a time-localized portion of a reference video that potentially matches the input video. A classifier is applied to each of the candidate segments to classify the segment as a matching segment or a non-matching segment. A result is then outputted identifying a matching portion of a reference video from the reference video set based on the segments classified as matches.