Real-Time Video Targeting System for Dynamic Content Personalization
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Solution Overview
Problem
Conventional video production methods render scenes from fixed camera viewpoints and angles, limiting personalization and dynamic content adaptation for viewers based on their profiles and preferences.
Innovation Solution
A real-time video targeting system leverages network-based computation resources to dynamically generate and render personalized video content by replacing objects and modifying scene elements in pre-recorded videos based on viewer profiles, using 2D or 3D graphics data, and streaming the modified content in real-time to client devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional video production methods are used to render scenes from fixed camera viewpoints, then manufacturing precision and reliability are maintained, but adaptability and personalization capability deteriorate
Solution Approach 1:
The video content is segmented into discrete objects that can be individually identified, extracted, and replaced. The system divides the video stream into object instances that can be independently manipulated based on viewer profiles, allowing personalized content substitution without re-rendering entire scenes.
Solution Approach 2:
The system creates copies of identified video objects and replaces them with alternative content from a content library. Instead of modifying the original video, it generates personalized versions by substituting object copies with targeted alternatives based on viewer preferences and demographic information.
2Productivity
If real-time rendering is implemented to dynamically modify video content, then adaptability and personalization are improved, but processing time and computational resources increase
Solution Approach 1:
Objects and scenes are pre-identified and tagged during video encoding with metadata that enables rapid retrieval and replacement. The system performs preliminary segmentation and object detection during the encoding phase, so that real-time personalization only requires content substitution rather than full scene re-rendering.
Solution Approach 2:
Instead of re-rendering entire video scenes, the system applies modifications only to specific local regions where objects need to be replaced or customized. This localized approach reduces computational overhead by focusing processing resources only on the portions of the video that require personalization.
3Adaptability or versatility
If fixed camera viewpoints are used in conventional video production, then manufacturing simplicity is maintained, but adaptability for different viewer perspectives deteriorates
Solution Approach 1:
The system dynamically adjusts video content based on real-time viewer information such as demographic data, device type, and location. Instead of creating multiple static versions for different viewpoints, it dynamically selects and replaces objects in the video stream to match the current viewer's profile and context.
Solution Approach 2:
The system changes video content parameters by substituting objects with alternatives from a content library based on viewer characteristics. It modifies the video stream by altering which objects are displayed, their properties, and their placement, while maintaining the original scene structure and camera viewpoints.
Data Source
AI summary
A real-time video targeting (RVT) system may leverage network-based computation resources and services, available 2D or 3D model data, and available viewer information to dynamically personalize content of, or add personalized content to, video for particular viewers or viewer groups. When playing back pre-recorded video to viewers, at least some objects or other content in at least some of the scenes of the video may be replaced with objects or content targeted at particular viewers or groups according to profiles or preferences of the viewers or groups. Since the video is being rendered and streamed to different viewers or groups in real-time by the network-based computation resources and services, any given scene of a video may be modified and viewed in many different ways by different viewers or groups based on the particular viewers' or groups' profiles.