Dynamic Media Effect Application in Video Streams
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Solution Overview
Problem
Existing video communication technologies lack dynamic, personal, and social media effects that can be automatically or manually applied based on user interactions, viewer engagement, and contextual information, limiting the immersive and interactive experience.
Innovation Solution
A system that applies media effects dynamically by aggregating user inputs such as interactions, viewer engagement, and contextual data from sensors and social networks, allowing for real-time modification of video streams with overlays, backgrounds, and object recognition to create a more immersive experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional video communication systems are used, then basic communication functionality is maintained, but dynamic and personalized media effects cannot be applied
Solution Approach 1:
The system segments media effects into predefined categories (overlays, filters, animations, backgrounds) that can be independently selected and applied. Each effect type is processed separately through its own pipeline, allowing the system to handle complexity in a modular fashion while providing diverse adaptive effects
Solution Approach 2:
The system pre-processes video frames to detect faces, objects, and contextual elements before media effects are applied. Detection results are prepared in advance and used to automatically select appropriate effects, enabling dynamic adaptation without real-time complex decision-making during effect application
2Extent of automation
If manual media effect application is used, then simple effects can be applied, but automatic context-based effects cannot be implemented
Solution Approach 1:
The system continuously monitors video content for contextual information such as detected objects, facial expressions, and scene characteristics. This feedback loop automatically triggers appropriate media effects based on the detected context, enabling intelligent automatic effect application that responds to real-time video content analysis
Solution Approach 2:
The system automatically selects and applies media effects without requiring user intervention. By using detected contextual information to self-determine appropriate effects, the system eliminates the need for manual selection while maintaining context-appropriate effect application
3Adaptability or versatility
If basic video streaming is provided, then low bandwidth is required, but immersive and interactive experience cannot be achieved
Solution Approach 1:
Media effects are applied selectively to specific regions of the video stream, such as overlaying effects only on detected faces or objects rather than processing the entire frame. This localized approach enhances interactive and immersive experience in key areas while minimizing overall bandwidth consumption
Data Source
AI summary
Exemplary embodiments relate to techniques for applying media effects to a video stream. For example, media effects may be applied and/or altered based on input from viewers or participants in the video stream. Changes to the media effects may accumulate based on the inputs. In another example, viewership numbers or engagement with a user applying a media effect may alter the media effect. In a broadcast context, actions of the broadcast audience (e.g., as measured by polling) may affect the broadcast and hence the broadcaster. Object recognition and/or people recognition may be applied to cumulatively alter the media effects in an augmented reality context.