Video Stream Image Overlay Automation
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Solution Overview
Problem
Existing methods for overlaying images in video streams are manual and non-automatic, leading to inefficiencies in mass video processing and delayed responses to changing customer demands, resulting in inaccurate and untimely image overlay.
Innovation Solution
A method and system that utilize image element signatures generated through pattern recognition and matching algorithms to automatically overlay images in video streams, allowing for dynamic positioning and database-driven matching to enhance the overlay process, ensuring photorealistic and interactive image integration without disrupting video viewing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operations are used to extract and overlay images in video streams, then the overlay process can be performed with simple system requirements, but the productivity and response time are significantly reduced
Solution Approach 1:
The system performs automatic image element signature generation through pattern recognition and automated matching with images to be overlaid, eliminating the need for manual extraction and editing operations. The automated workflow includes extracting image frames, generating signatures via pattern recognition, matching with target images, and performing overlay operations without human intervention, thereby significantly improving productivity while maintaining manageable system complexity through modular architecture
Solution Approach 2:
The patent replaces manual mechanical operations (operator extraction, selection, and editing) with automated computational processes including pattern recognition algorithms, signature generation, and automated matching systems. This substitution of manual mechanical work with automated information processing systems resolves the contradiction by enabling high-speed automated processing without requiring complex manual intervention systems
2Measurement precision
If automated image overlay is implemented using pattern recognition and matching algorithms, then the productivity and accuracy are improved, but the device complexity increases
Solution Approach 1:
The system transforms the complex image matching problem into a parameter-based signature comparison task. By extracting key visual features and representing them as compact signatures, the system achieves accurate matching through parameter comparison rather than full image analysis. This parameter transformation approach maintains high matching accuracy while reducing computational complexity compared to traditional automated methods
Solution Approach 2:
The patent extracts essential visual information from images and represents it as condensed signatures containing key identifying parameters. This extraction of critical features from complete images allows for accurate matching without processing the entire image data, thereby achieving high precision while managing algorithmic complexity through selective feature extraction rather than comprehensive analysis
3Loss of time
If manual video editing operations are performed to overlay images, then the system requirements remain low, but the response time to customer demand changes is delayed
Solution Approach 1:
The system performs preliminary automated operations including image frame extraction, signature generation, and matching preparation in advance, enabling rapid response when customer demand changes. The automated pipeline pre-processes video content and maintains ready-to-use signatures, so that when overlay requests arrive, the system can quickly match and execute without manual intervention delays, thus reducing response time while maintaining operational simplicity through automation
4Manufacturing precision
If non-automatic operations with scheduled rules are used for image overlay, then the system structure remains simple, but the manufacturing precision and overlay accuracy are reduced
Solution Approach 1:
The system incorporates feedback mechanisms where pattern recognition results are used to generate signatures that are then matched with images to be overlaid, and the matching results guide the overlay placement. This feedback loop ensures accurate overlay positioning by continuously refining the matching process based on extracted visual features, achieving high manufacturing precision while managing system structure complexity through structured feedback pathways rather than complex ad-hoc control
Data Source
AI summary
The present invention provides a method and a system for overlaying an image in a video stream. The method comprising steps of: acquiring an image element signature including at least one image element from the video stream; determining whether the image element signature matches an image to be overlaid; and overlaying the image when the image element signature is determined to match the image to be overlaid.