Real-Time Video Summarization via Content Feature Extraction
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Solution Overview
Problem
Conventional video summarization systems generate summaries with delays, require post-processing, and are inefficient in memory usage, limiting immediate availability and flexibility in generating summaries of varying durations.
Innovation Solution
A real-time data summarization system that selects and generates summaries during data stream reception, using content analysis signals like visual activity and luminance to prioritize data stream portions, allowing for multiple summaries of different durations without additional computational complexity, and utilizing a controlled memory for efficient storage and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional summarization systems perform post-processing after recording to generate summaries, then the summary generation is thorough and complete, but the summary is not immediately available and requires additional processing time
Solution Approach 1:
The system extracts content features and generates summaries during the recording process itself, rather than performing post-processing after recording completes. The summarization function is executed preliminarily alongside the main recording operation, ensuring summaries are immediately available without delaying the recording process.
Solution Approach 2:
The summarization process runs continuously during recording, maintaining parallel processing of both full content recording and summary generation. This continuous action ensures that summary generation is integrated into the recording workflow rather than being a separate post-processing step.
2Quantity of substance
If conventional summarization systems extract content features after recording or during recording in compressed domain, then memory usage is reduced, but the summarization process cannot be completed in real-time
Solution Approach 1:
The system performs content feature extraction during the recording process itself, extracting features from incoming video data as it arrives. This preliminary extraction during recording enables real-time summary generation without requiring additional memory storage of the entire video content.
Solution Approach 2:
The system extracts only the essential content features needed for summarization during recording, rather than storing and processing the complete video data. This selective extraction of relevant features reduces memory requirements while maintaining real-time processing capability.
3Measurement precision
If conventional summarization systems generate a single summary after recording, then the summary represents the entire content accurately, but the system lacks flexibility to provide summaries of different durations
Solution Approach 1:
The system segments the video content into multiple atomic units based on extracted content features during recording. These segmented units can be independently selected and combined to create summaries of various durations, providing flexibility while maintaining accurate content representation through feature-based selection.
Solution Approach 2:
The system dynamically adjusts summary composition by selecting from pre-segmented content units based on desired summary duration. This dynamic selection process allows the generation of summaries in different lengths while maintaining content accuracy through feature-based prioritization of important segments.
4Measurement precision
If conventional summarization systems perform comprehensive content analysis after recording, then the summary quality is high, but the processing time and computational resources increase
Solution Approach 1:
The system performs comprehensive content analysis during the recording process itself, extracting features and analyzing content as video data arrives. This preliminary analysis during recording produces high-quality summaries without requiring additional processing time after recording completes.
Solution Approach 2:
The content analysis and summarization processes run continuously during recording, maintaining parallel execution of both full content capture and summary generation. This continuous processing ensures high summary quality through thorough analysis while avoiding additional post-processing delays.
Data Source
AI summary
In order to further develop a method for summarizing at least one data stream (12) as well as a corresponding data summarization system (100) comprising at least one receiving means (10) for receiving at least one data stream (12) in such way that at least one summary is available immediately after receiving of the data stream (12), in particular immediately after content acquisition and/or recording and/or encoding and/or decoding of the data stream without any post-processing operation, it is proposed to provide—at least one selecting means (30) for selecting part (32, 32′) of the data stream portions and at least one processing means (70) for generating at least one summary by summarizing at least part of the selected data stream portions (32′) in particular until at least one predetermined summary volume is obtained, wherein the summary is generated during the receiving of the data stream (12).