Video Cutting System Preserving Narrative Continuity via AI Analysis
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Solution Overview
Problem
Current video cutting techniques fail to effectively handle user-initiated interruptions, leading to a loss of context and disruption of narrative continuity, as they do not adequately consider critical narrative elements like context, action, and dialogue.
Innovation Solution
A dynamic, user-defined film-slicing approach that utilizes advanced Artificial Intelligence (AI), histogram analysis, and statistical techniques to intelligently divide video content into user-specified blocks while preserving narrative continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional frame-by-frame video segmentation is used, then video can be divided into segments, but narrative continuity and context are lost
Solution Approach 1:
The system performs preliminary analysis of the video content before segmentation by training AI models to recognize narrative elements, scene transitions, and contextual relationships. This preliminary understanding allows the system to make informed segmentation decisions that preserve narrative continuity while maintaining efficiency.
Solution Approach 2:
The patent introduces an AI-based intermediary layer that analyzes video frames, subtitles, and audio content to identify meaningful segmentation points. This intermediary system acts as a mediator between raw video data and segmentation decisions, ensuring that cuts occur at appropriate narrative boundaries rather than arbitrary frame intervals.
2Ease of operation
If user-defined interval cutting is applied, then video can be segmented according to user specifications, but critical narrative elements may be disrupted
Solution Approach 1:
The system incorporates feedback mechanisms where AI models continuously analyze video content and provide recommendations to users about optimal segmentation points. The system evaluates user-defined cut points against narrative structure and provides feedback on whether proposed segments will maintain coherence, allowing users to adjust their specifications while preserving narrative integrity.
Solution Approach 2:
The patent implements dynamic segmentation boundaries that can adjust based on narrative content. Rather than fixed user-defined intervals, the system allows segmentation points to shift dynamically to align with scene transitions, dialogue boundaries, and narrative pacing, balancing user specifications with narrative requirements.
3Device complexity
If simple object or character recognition is used, then basic frame analysis can be performed, but comprehensive storyline understanding is insufficient
Solution Approach 1:
The patent merges multiple analysis modalities including object recognition, character tracking, subtitle analysis, audio processing, and scene transition detection into a unified AI framework. This combination allows the system to comprehend storyline context by synthesizing information from diverse sources rather than relying on single-modality analysis.
Solution Approach 2:
The system employs composite AI models that integrate different types of analysis capabilities (computer vision, natural language processing, audio analysis) into a unified framework. This composite approach enables comprehensive storyline understanding by combining the strengths of multiple specialized models rather than using a single simple recognition system.
Data Source
Figure 1
AI summary
A method, system, and computer programs for cutting videos are proposed. The method comprises performing by one or more processors the following steps: obtaining a video to be cut; obtaining at least one desired cut-off point for said video; executing a decision-making procedure to determine whether the desired cut-off point is feasible. The decision-making procedure, for each pair of consecutive video frames contained within the desired cut-off point, comprises checking whether there is an active subtitle during the desired cut-off point, disregarding the desired cut-off point if there is an active subtitle; assessing video frame's distance, similarity, and quality characteristics of a scene taking place in the desired point using image analysis techniques and/or one or more artificial intelligence techniques; comparing the result of the assessing step with a given threshold; determining feasibility of the desired cut-off point based on a result of said comparison.