AI Video Summary Generation for Real-Time Multimedia Content

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Solution Overview

Problem

Existing AI-based content summarization solutions primarily provide textual summaries, which are not effective for visual thinkers and learners, and there is a need for real-time video summary generation that accurately processes and summarizes multimedia content.

Innovation Solution

A system that utilizes generative AI models to process different data types (text, audio, video) separately, extracting key information to generate a comprehensive video summary, incorporating contextual features and allowing user interaction for editing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If AI-based content summarization is implemented using existing solutions, then content processing automation is achieved, but the summaries are only in text format which is not effective for visual thinkers and learners

Engineering Contradiction:

Improvesummary format adaptabilityVSAvoiduser effectiveness

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system segments the summary generation process into separate processing streams for different media types (text, audio, video). Each stream processes its respective content type and generates appropriate visual summaries, allowing the system to adapt to different user preferences while maintaining ease of use through automated processing.

Inventive Principle:

Principle #1Segmentation

2Ease of operation

If video summary generation is implemented to serve visual learners, then user effectiveness is improved, but processing complexity and resource requirements increase

Engineering Contradiction:

Improveuser effectivenessVSAvoidprocessing complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system divides video processing into segmented operations: extracting key frames, generating text transcripts, creating summaries, and assembling final video summaries. This segmentation reduces processing complexity by handling each aspect separately rather than processing the entire video monolithically.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system extracts only the essential elements from video content (key frames, critical text transcripts, main themes) rather than processing the entire video. This extraction approach maintains user effectiveness while significantly reducing processing complexity and resource requirements.

Inventive Principle:

Principle #2Taking out (Extraction)

3Measurement precision

If comprehensive video summaries are generated with contextual features, then summary accuracy is improved, but processing time and resource consumption increase

Engineering Contradiction:

Improvesummary accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-processing video content to extract key frames and generate text transcripts before summary generation. This preliminary processing organizes the data in advance, enabling faster and more accurate summary creation without requiring excessive processing time during the actual summarization phase.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system extracts only the most relevant contextual features and key elements from the video content rather than analyzing every detail. This selective extraction maintains summary accuracy by focusing on essential information while reducing processing time and resource consumption.

Inventive Principle:

Principle #2Taking out (Extraction)

4Productivity

If real-time video summary generation is implemented, then productivity is improved, but processing speed requirements and resource consumption increase

Engineering Contradiction:

Improvecontent consumption productivityVSAvoidprocessing speed

Core Design Contradiction:

ProductivityVSSpeed

Solution Approach 1:

The system segments real-time video processing into parallel streams that can operate simultaneously. Text transcript generation, key frame extraction, and summary generation proceed in parallel rather than sequentially, enabling real-time performance while maintaining processing speed within acceptable limits.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements partial processing by generating summaries of the most important portions of video content in real-time rather than attempting to process every detail. This approach maintains productivity benefits while keeping processing speed requirements manageable through selective processing of critical content.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20250358492A1Ai-based video summary generation for content consumption

Publication Date: 2025.11.20 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A data processing system implements receiving content and a call requesting a generative model to generate a video summary of the content; constructing a prompt including the content and instructions to the model to identify semantic context of the content, to identify a text data item, an audio data item, and/or a video data item embedded in the content to generate a text transcript of the audio data item and/or the video data item, or a textual description of the video data item, to summarize the text data item, the text transcripts, and/or the textual description as a summary of the content based on the semantic context, and to generate the video summary based on the summary and a portion of the text data item, the audio data item, and/or the video data item; providing the first prompt to the generative model; providing the video summary to a client device for presentation.