Video Segment Identification via Dynamic Characterization

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Solution Overview

Problem

The sheer quantity of media content available online makes it challenging for users to identify and select content that suits their preferences, as existing methods rely on insufficient or mischaracterized descriptions provided by content owners.

Innovation Solution

A system and method for video segment identification and organization based on dynamic characterizations, where a characteristics component analyzes videos to determine characteristics such as category, type, person, or object, and a segmenting component segments the video accordingly, with indicators associated with these characteristics for playback control and user navigation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If content owners provide descriptions or tags to assist users in identifying media content, then users can locate content more easily, but the descriptions may be insufficient or mischaracterized, leading to inaccurate content identification

Engineering Contradiction:

Improvecontent identificationVSAvoidcontent characterization accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent introduces an automated content analysis system as an intermediary between content owners and users. This system analyzes video content using computer vision and audio processing to generate accurate metadata and tags, serving as a mediator that resolves the conflict between user-friendly content identification and accurate content characterization. The automated analysis objectively extracts content features without relying on potentially inaccurate owner-provided descriptions.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the manual mechanical process of content owners providing descriptions with an automated computational analysis system. This substitution uses algorithms for video frame analysis, audio transcription, and content classification to generate metadata automatically, eliminating the human error and inconsistency inherent in manual tagging while improving both ease of operation and measurement precision.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Quantity of substance

If the quantity of media content available online increases, then users have more content to choose from, but it becomes more challenging to identify and select content that suits their preferences

Engineering Contradiction:

Improvemedia content availabilityVSAvoidcontent selection difficulty

Core Design Contradiction:

Quantity of substanceVSDifficulty of detecting and measuring

Solution Approach 1:

The patent applies segmentation by dividing large video content into smaller, analyzable units such as scenes, segments, or key moments. The system processes content in manageable portions, extracting features from individual segments and organizing them with precise metadata. This segmentation approach makes it feasible to analyze and organize vast quantities of media content while maintaining high identification accuracy through structured metadata generation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The automated analysis system acts as an intermediary that processes the overwhelming quantity of media content and transforms it into organized, searchable formats with accurate metadata. This intermediary layer filters, categorizes, and tags content systematically, reducing the complexity of content selection for users while preserving the full quantity of available content.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If automated analysis is used to determine video characteristics, then content identification accuracy is improved, but processing time and computational resources increase

Engineering Contradiction:

Improvevideo characteristic accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent implements partial action by analyzing only the most relevant portions of video content rather than processing every frame uniformly. The system identifies key segments containing important visual or audio information and focuses computational resources on those areas, achieving high measurement precision while reducing overall processing time through selective analysis of critical content portions.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system performs preliminary analysis by extracting basic video characteristics early in the processing pipeline, such as initial frame analysis for scene detection or audio level analysis for segment identification. These preliminary actions prepare the data for more detailed analysis later, enabling efficient processing by establishing a foundation of key characteristics before committing extensive computational resources.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS8942542B1Video segment identification and organization based on dynamic characterizations

Publication Date: 2015.01.27 GOOGLE LLC

AI summary

This disclosure relates to video segment identification and organization based on dynamic characterizations. A characteristics component analyzes a video, and determines a set of video characteristics based at least in part on the analysis. The video characteristics include but are not limited to a category, a type, an identity of a person, and/or an identity of an object. A segmenting component segments the video based in part on the set of video characteristics, and an indicator component associates indicators corresponding to respective video characteristics with the corresponding video segments.