On-Demand Video Rendering with Avatar Replacement
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Solution Overview
Problem
Social networking systems face challenges in generating and delivering personalized video content featuring users' avatars in real-time, as existing methods require pre-generation of content and struggle to keep up with dynamic user interactions and updates.
Innovation Solution
The system renders video content on demand by replacing placeholder avatars with users' avatars in media content items, utilizing a content controller system with a delivery server and rendering server to minimize latency and simplify animation processes, allowing for real-time personalized content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If pre-generation of video content is used, then content can be delivered quickly, but the system cannot keep up with dynamic user interactions and updates
Solution Approach 1:
The video content is segmented into multiple frames that can be independently processed and rendered. The system separates the static media content from the dynamic avatar replacement, allowing the base video to be pre-generated while individual frames are rendered on-demand with user-specific avatars. This segmentation enables both quick delivery of base content and adaptability to dynamic user interactions.
Solution Approach 2:
The system performs preliminary action by pre-generating the base video content with placeholder avatars, then prepares the infrastructure to render specific frames on-demand. Media content items are pre-prepared with placeholder avatars in specific locations, and the system pre-configures the rendering pipeline to efficiently replace these placeholders with user-specific avatars when needed, combining the benefits of pre-generation with on-demand customization.
2Adaptability or versatility
If real-time avatar replacement is implemented, then personalized content can be delivered on-demand, but content generation delays increase
Solution Approach 1:
The video is divided into discrete frames that can be independently rendered. Instead of rendering the entire video in real-time, the system only renders specific frames that need customization, significantly reducing the time required for personalization while maintaining the ability to deliver personalized content on-demand.
Solution Approach 2:
The system performs preliminary rendering of frames that can be reused across multiple users. By pre-rendering frames with placeholder avatars and preparing the rendering pipeline in advance, the system minimizes the time required for real-time avatar replacement, achieving both personalization and speed.
3Manufacturing precision
If complex animation processes are used, then detailed and realistic avatars can be generated, but the animation process becomes complicated and time-consuming
Solution Approach 1:
The system extracts the avatar replacement function from the complex animation process. Instead of using complex real-time animation to generate avatars, the system uses pre-computed or cached avatar images and simply replaces them in the video frames. This extraction simplifies the overall process while maintaining high avatar rendering quality through the use of detailed pre-generated avatars.
Solution Approach 2:
The system uses copying by utilizing pre-generated avatar images and placeholder avatars that are reused across multiple video frames and users. Rather than creating complex animations for each avatar instance, the system copies and replaces pre-computed avatar images, significantly simplifying the process while maintaining quality through the use of high-resolution pre-generated avatars.
4Adaptability or versatility
If personalized video content is generated for each user, then user engagement increases, but system resources are consumed excessively
Solution Approach 1:
The system segments the video rendering process to only process frames that require customization. By identifying and rendering only the necessary frames with user-specific avatars rather than the entire video for each user, the system significantly reduces computational resources while maintaining high personalization levels that enhance user engagement.
Solution Approach 2:
The system performs preliminary action by pre-generating video content with placeholder avatars and pre-preparing the rendering infrastructure. This allows the system to serve multiple users with personalized content using the same computational resources, as the heavy lifting is done once with placeholder avatars rather than creating entirely new videos for each user.
Data Source
AI summary
Method to generate frames on demand starts with a system receiving a request for a media content item from a client device. The request includes a media content identification and a main user identification. The system transmits to the client device a playlist including a first set of media content item segments. While the first set of media content item segments is being displayed on the client device, the system renders a second set of media content item segments using the media content identification and the main user identification. Rendering the second set of media content item segments can include rendering a main user avatar based on the main user identification and incorporating the main user avatar into the second set of media content item segments. The system then updates the playlist to include the second set of media content item segments. Other embodiments are disclosed herein.