Automated Digital Composite Placement in Video Media
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Solution Overview
Problem
Existing digital media compositing systems for OTT platforms face challenges in scaling personal media overlays due to the need for manual artist intervention and individual customization, making it difficult to efficiently apply custom composites across widely distributed content.
Innovation Solution
An automated system utilizing an Automated Placement Opportunity Identification engine and Placement Insertion Interface, which employs neural networks for identifying placement opportunities and integrating creative graphics into digital media, allowing for programmatic compositing and previewing of overlays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual artist intervention is used for compositing, then customization quality is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces the manual mechanical process of artists using GUI tools with an automated computer vision system. The system uses machine learning models to detect placement opportunities, segment objects, and generate composites automatically, eliminating the need for manual artist intervention while maintaining quality through algorithmic precision.
Solution Approach 2:
The system enables self-service compositing where the software automatically performs detection, segmentation, and composite generation without human intervention. The automated pipeline processes content end-to-end, allowing the system to serve itself rather than requiring external artist input for each composite operation.
2Adaptability or versatility
If individual customization is applied to each consumer, then consumer experience is improved, but device complexity deteriorates
Solution Approach 1:
The patent segments the compositing process into distinct automated modules: placement opportunity detection, object segmentation, composite generation, and quality assessment. This modular architecture enables individual customization for each consumer while managing system complexity through organized, reusable components that can be independently developed and maintained.
Solution Approach 2:
The system enables personalization by dynamically changing parameters such as composite selection, placement position, and graphic overlay based on consumer data and preferences. The automated system adjusts these parameters programmatically for each user without requiring complex manual configuration, thus improving adaptability while controlling complexity.
3Measurement precision
If manual identification of composite opportunities is performed, then detection precision is improved, but loss of time deteriorates
Solution Approach 1:
The patent implements periodic action through automated batch processing of content to identify placement opportunities. The system continuously scans and analyzes digital content at regular intervals, using machine learning models to detect suitable locations for composites automatically, thereby maintaining high detection accuracy while eliminating the time loss associated with manual identification.
Solution Approach 2:
The system performs preliminary action by pre-processing content to pre-identify potential placement opportunities before actual compositing occurs. The automated detection system analyzes content in advance, segments objects, and prepares candidate locations, so that when compositing is needed, the work is already substantially complete, maintaining precision while minimizing time loss.
Data Source
AI summary
A system and method for inserting a composited image or otherwise generated graphic into a selected video by way of a programmatic process. According to some embodiments, a system may comprise an Automated Placement Opportunity Identification (APOI) engine, a Placement Insertion Interface (PII) engine, a preview system, and an automated compositing service. The system finalizes a graphic composite into a video and provides a user with a preview for final export or further manipulation.