Media Editing System Using Edit Attribute Transfer
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Solution Overview
Problem
Existing media editing applications require users to download specific applications and perform complex steps to apply similar edit attributes, making it difficult for users to recreate effects on new media, especially for amateur users who are not technically aware of editing operations.
Innovation Solution
A method and system that allow users to transfer compatible edit attributes from a reference media to a target media using a processing engine and edit transfer engine, which identifies dominant edit attributes, performs compatibility checks, and applies selected attributes using convolutional neural networks and other machine learning techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users want to apply similar edit attributes on different media, then the editing effect can be consistent, but users have to download multiple specific media editing applications and perform complex editing operations
Solution Approach 1:
The patent creates a universal media editing system where a single application can handle multiple edit attributes across different media types. The system extracts edit attributes from reference media and applies them to target media, eliminating the need for multiple specialized applications and enabling consistent editing effects across diverse media.
Solution Approach 2:
The system copies edit attributes from reference media to target media by extracting dominant edit attributes and transferring them. This allows users to recreate the same editing effect on different media without manually performing complex editing operations, maintaining consistency while simplifying the process.
2Manufacturing precision
If multiple edit attributes are applied on media to generate a pleasing effect, then the aesthetic quality improves, but the complexity of editing operations increases making it difficult for amateur users
Solution Approach 1:
The system performs automatic background replacement and edit attribute extraction without requiring user intervention in complex editing operations. The processing engine automatically identifies dominant edit attributes from reference media and applies them to target media, enabling amateur users to achieve high aesthetic quality without technical expertise.
Solution Approach 2:
The system performs preliminary extraction and analysis of edit attributes from reference media before applying them to target media. This pre-processing step identifies dominant edit attributes and prepares them for transfer, simplifying the user's task to merely selecting reference and target media while maintaining high aesthetic quality.
3Adaptability or versatility
If users want to recreate similar memories with existing contents from social media, then the personalization of content improves, but users may not be aware of which application can create such effects
Solution Approach 1:
The system provides a universal platform that can process various media types from social media and apply edit attributes across different formats. This versatility allows users to personalize content from diverse sources without needing to know which specific application handles which media type, improving accessibility while maintaining personalization.
4Device complexity
If existing media editing applications enable limited operations such as transferring texture, then the simplicity of the application is maintained, but the functionality is restricted
Solution Approach 1:
The system extracts dominant edit attributes from reference media, separating the essential editing characteristics from the source content. This extraction enables the application to transfer multiple types of edit attributes including effects, background blur, contrast, and texture, expanding functionality while maintaining a simple user interface where users only need to select reference and target media.
Data Source
Figure 1~2A
Figure 2B~3
Figure 4A~4B
AI summary
Methods and systems for performing editing operations on media are provided. A method includes receiving at least one reference media and at least one target media, identifying at least one dominant edit attribute of the at least one reference media, and performing a compatibility check to determine a compatibility of the at least one target media with the at least one dominant edit attribute of the at least one reference media. Based on results of the compatibility check, at least one compatible edit attribute is selected from the at least one dominant edit attribute, and the at least one compatible edit attribute is transferred from the at least one reference media to the at least one target media.