Dynamic Live Stream Occlusion for Privacy Protection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Live streaming platforms face challenges in ensuring privacy and appropriateness of content, as individuals may be broadcasted without consent, leading to potential privacy violations and exposure to inappropriate material.
Innovation Solution
A system and method for dynamic occlusion of live streaming video that uses real-time image occlusion technology to identify and obscure restricted content, such as individuals or actions, based on user-defined rules, social media connections, and viewer relationships, allowing for real-time processing and broadcasting with minimal latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time image occlusion technology is applied to identify and obscure restricted content in live streaming video, then privacy protection and content appropriateness are improved, but processing complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-defining restricted content categories and occlusion rules before live streaming begins. This allows the processing system to work with predefined parameters rather than creating rules in real-time, reducing computational complexity during actual streaming while maintaining reliable privacy protection
Solution Approach 2:
The live streaming video feed is segmented into discrete frames that are processed individually. Each frame is analyzed for restricted content independently, allowing parallel processing and reducing the computational burden on any single processing unit. This segmentation enables the system to handle high-volume video data while maintaining manageable processing complexity
2Reliability
If dynamic occlusion is applied to restricted content in live streaming video, then viewer experience and content safety are improved, but video processing time and latency increase
Solution Approach 1:
The patent replaces traditional mechanical video processing systems with AI-based automated content recognition and occlusion application. This substitution enables faster, more efficient processing of video content to identify and obscure restricted material while maintaining content safety, reducing the time penalty associated with dynamic occlusion
Solution Approach 2:
The system implements optimized processing pathways that skip unnecessary analysis steps for content that clearly does not contain restricted material. By rapidly identifying and bypassing safe content segments, the system minimizes processing time while maintaining thorough scrutiny of potentially restricted content, thus reducing overall latency
3Measurement precision
If AI-based automated content recognition is used to identify restricted content, then detection accuracy and privacy protection are improved, but computational resource consumption increases
Solution Approach 1:
The system applies partial action by using AI-based automated content recognition selectively rather than uniformly across all video content. It focuses computational resources on segments with higher probability of containing restricted material, using heuristics to identify and prioritize analysis of potentially problematic areas, thus maintaining high detection accuracy while reducing overall computational resource consumption
Data Source
AI summary
In an approach for dynamic occlusion of a live streaming video, a processor receives and processes a live streaming video. A processor determines whether any restricted content is in the live streaming video based on a set of user rules. A processor, in response to determining one or more restricted content being in the live streaming video, applies an occlusion to the one or more restricted content in the live streaming video. A processor broadcasts the live streaming video with the occlusion.