Video Assembly Application Using Organizing Elements
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Solution Overview
Problem
Users, both amateur and advanced, face challenges in efficiently assembling movies from large video libraries due to the cumbersome nature of video footage, where it is difficult to find relevant content quickly, leading to wasted time and potential exclusion of relevant content.
Innovation Solution
A video assembly application that allows users to assemble movies using an organizing element, such as event descriptions, visual elements, or audio profiles, to identify and select relevant video segments from a library, enabling efficient inclusion of desired content and exclusion of irrelevant parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually search through large video libraries to find relevant content, then they can ensure content is included, but the time required for assembly increases significantly
Solution Approach 1:
The video assembly system performs automatic content identification and segmentation without requiring manual user intervention. The system analyzes video content, identifies relevant segments based on user criteria, and assembles them automatically, making the system serve itself rather than requiring continuous user input and review.
Solution Approach 2:
The patent replaces manual mechanical searching and selection processes with automated computational analysis. Instead of users manually reviewing video content, the system uses automatic content analysis, pattern recognition, and algorithmic segmentation to identify and assemble relevant video segments, substituting human effort with computational processes.
2Manufacturing precision
If users manually review each video segment to ensure relevance, then content quality is maintained, but the complexity of the operation increases
Solution Approach 1:
The system automatically performs content analysis, relevance determination, and segment selection without requiring users to manually review each segment. The system serves itself by autonomously identifying relevant content and assembling it according to user-defined criteria, eliminating the need for manual verification while maintaining precision.
Solution Approach 2:
The system performs preliminary content analysis and pre-assembly of video segments before presenting the final result to the user. By automatically analyzing content, identifying relevant segments, and pre-assembling them in the correct sequence, the system prepares the final product in advance, requiring minimal user intervention and simplifying the overall operation.
3Manufacturing precision
If users selectively choose only relevant video segments, then the final movie quality improves, but the difficulty of identifying relevant content increases
Solution Approach 1:
The patent replaces manual content relevance detection with automated computational analysis. The system uses algorithms to analyze video content, identify relevant segments based on user criteria, and determine their significance automatically, substituting the difficult manual detection process with computational methods that can efficiently evaluate content relevance.
Solution Approach 2:
The system introduces an intermediary automated analysis layer between the user and the video content. This intermediary performs content analysis, relevance determination, and segment identification, translating user requirements into specific content selections without requiring users to directly evaluate and detect relevance in raw video footage.
4Adaptability or versatility
If users assemble movies from large video libraries without automation, then they maintain full control over content selection, but the productivity of the process decreases
Solution Approach 1:
The system performs automatic content identification, segmentation, and assembly without requiring continuous user control and input. Users define their criteria once, and the system autonomously completes the entire assembly process, maintaining user control over the outcome while dramatically increasing productivity through automated execution.
Solution Approach 2:
The system performs preliminary analysis of the entire video library, pre-identifies relevant segments, and pre-assembles them according to user criteria before the user initiates the final assembly. This preliminary preparation work is done automatically in advance, enabling rapid final assembly while maintaining user control over the selection criteria and final output.
Data Source
AI summary
A computer-implemented method involves accessing a library of video segments, receiving a user instruction to assemble a movie related to an organizing element that includes a video segment from the library of video segments, relating the organizing element to a video segment in the library of video segments, determining, based on relating the organizing element to the video segment in the library of video segments, whether the video segment should be added to a list of selected segments used to assemble the movie, selectively adding the video segment to the list of selected segments in response to determining that the video segment should be added, and assembling the movie using the list of selected segments.