Real-Time Video Censoring via VLC Entity Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video capture and sharing technologies fail to effectively censor protected content in real-time, requiring labor-intensive post-processing and resource-heavy techniques to obscure sensitive or copyright-protected information from unauthorized viewers.
Innovation Solution
Employing Visual Light Communication (VLC) technology to transmit entity information about protected content, which is used to identify and modify video recordings in real-time, replacing sensitive information with graphical elements to obscure it from view, ensuring privacy and confidentiality during live video streaming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If post-processing techniques are used to blur-out protected content, then privacy and confidentiality are maintained, but processing resources and time-delays increase significantly
Solution Approach 1:
The patent applies preliminary action by detecting protected content during video capture and applying censorship in real-time before the video is fully recorded or transmitted. This prevents the need for later post-processing, thereby maintaining privacy while avoiding the resource-intensive and time-consuming nature of post-processing operations.
Solution Approach 2:
The patent replaces manual post-processing operations with automated real-time detection and censorship systems. Entity recognition algorithms and content analysis performed during video capture substitute for labor-intensive manual editing, significantly improving processing efficiency while maintaining reliable privacy protection.
2Loss of time
If real-time censorship is implemented, then processing time is reduced, but device complexity and resource requirements increase
Solution Approach 1:
The patent segments the censorship function into distinct modular components: entity recognition module, content analysis module, censorship decision module, and video processing module. This segmentation allows real-time processing by dividing the complex task into manageable stages that can be executed efficiently and independently.
Solution Approach 2:
The patent introduces intermediary elements such as entity recognition algorithms and content analysis filters that act as mediators between video capture and final censorship. These intermediaries enable automated real-time detection and decision-making, reducing the need for complex manual intervention while maintaining effective censorship.
3Measurement precision
If manual post-processing is used to censor video content, then censorship accuracy is maintained, but labor input and processing resources increase
Solution Approach 1:
The patent implements self-service by enabling the video system to automatically detect protected content, make censorship decisions, and apply censorship filters without human intervention. The entity recognition algorithms and content analysis systems perform the censorship function autonomously, maintaining accuracy while eliminating labor-intensive manual operations.
Solution Approach 2:
The patent employs feedback mechanisms where entity recognition results and content analysis outcomes feed into automated censorship decision systems. This feedback loop enables the system to continuously adjust and refine censorship accuracy based on detected content characteristics, maintaining high precision while operating automatically without manual input.
Data Source
AI summary
Censoring a video recording of an environment, the environment containing a protected entity displaying protected content to be censored. Video of the environment is processed in accordance with an entity recognition process to identify the presence of at least part of an entity in the environment. It is determined if the identified entity is to be censored based on based on entity information of a received VLC signal. Based on the identified entity being determined to be censored, the video recording is modified to replace at least a portion of the identified entity with a graphical element adapted to obscure the portion of the identified entity in the video stream. By modifying a video stream to obscure an entity, protected content in the environment may be prevented from being displayed to a viewer of the video recording.