Automated Video Material Matching for Placeable Region Synthesis
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Solution Overview
Problem
Existing video processing methods require manual intervention for information implantation, which is inefficient and lacks intelligence in matching video content with implantable materials.
Innovation Solution
A method and apparatus for automatically identifying implantable areas in source videos and matching target materials based on feature labels, enabling bidirectional matching between source videos and objects to generate synthesized videos tailored to user interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing is used for information implantation in videos, then the precision of material matching can be maintained through human judgment, but the productivity and efficiency are significantly reduced due to labor-intensive operations
Solution Approach 1:
The system enables automated self-matching between implantable materials and video content through AI algorithms. The matching module automatically analyzes video semantics, identifies implantable areas, and selects appropriate materials without requiring manual intervention, thus achieving both high efficiency and intelligent matching precision
Solution Approach 2:
The patent replaces manual mechanical processing with automated computational systems. AI models and algorithms substitute human operators in the material selection and implantation process, maintaining matching quality while dramatically improving processing speed and productivity
2Productivity
If automated processing is introduced to improve video processing efficiency, then the productivity increases, but the complexity of the system increases due to the need for AI models and algorithms
Solution Approach 1:
The system is divided into distinct functional modules: video analysis module, implantable area detection module, material matching module, and synthesis module. Each module performs a specific task independently, which simplifies the overall system architecture and makes the complexity manageable through modular design
Solution Approach 2:
The AI models and algorithms are designed to perform multiple functions: semantic analysis, area detection, material matching, and synthesis. This multi-functionality reduces the need for separate specialized systems, thereby managing complexity while maintaining high productivity
3Device complexity
If manual video processing is used for information implantation, then the device complexity remains low with simple processing workflows, but the loss of time increases due to labor-intensive operations
Solution Approach 1:
The automated system enables continuous processing of videos through streamlined workflows. Multiple videos can be processed in sequence without interruption, and the system can operate continuously without fatigue, significantly reducing total processing time while maintaining manageable complexity through automation
Data Source
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AI summary
The present invention relates to a video processing method, comprising: building an object material resource library used for storing objects, attribute information, materials, description information and correspondence relationships thereof; building a source video resource library used for storing source videos, placeable regions, feature tags and correspondence relationships thereof; on the basis of a matching rule, matching a source video suitable for placement and a target placeable region of the source video for a target object, or matching an object suitable for placement and a material of the object for a target source video; and placing the material of the object to the placeable region of the source video to obtain a synthesized video. The present invention realizes the automatic placement of a matched object in a source video, thereby reducing labor cost, and improving the video processing efficiency.