Privacy-Preserving Video Capture with Pre-Transmission Object Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video conferencing technologies struggle with privacy concerns as they often require post-processing of video streams on servers, leading to potential privacy risks and inefficiencies in handling unknown or unanticipated sensitive objects.
Innovation Solution
A user-controlled system that generates filtered video streams by identifying and excluding unauthorized objects based on user-defined policies, using devices to apply privacy settings before transmission, and allowing for real-time or post-processing updates to ensure only approved content is shared.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If post-processing solutions are used to remove sensitive objects from video streams, then privacy protection is improved, but the video conference must be stored on a server first which creates privacy risks and delays processing
Solution Approach 1:
The system performs object identification and filtering actions before the video stream is stored on the server. By detecting sensitive objects and removing them in advance (during transmission or at the edge device), the system eliminates the need to store unfiltered video content, thus resolving the contradiction between privacy protection and processing delay.
Solution Approach 2:
The patent introduces an intermediary filtering mechanism that operates between the camera and the server/storage system. This intermediary component (implemented as edge computing devices or local processing units) performs the sensitive object detection and removal before data reaches the server, eliminating the privacy risk of storing unfiltered videos while maintaining processing efficiency.
2Adaptability or versatility
If blacklisting methods are used to remove identified objects, then known sensitive objects can be removed, but unknown or unanticipated objects cannot be filtered out effectively
Solution Approach 1:
Instead of using blacklisting (removing known objects) or whitelisting (showing only approved objects), the patent inverts the approach by using a positive identification system that detects and removes objects based on their sensitive characteristics. The system identifies objects by their visual features and compares them against a database of known sensitive object types, enabling it to handle unknown objects through pattern recognition rather than relying on pre-defined blacklists.
Solution Approach 2:
The system changes the filtering parameters from static blacklisted object IDs to dynamic visual feature matching. By analyzing visual parameters (color, shape, texture, motion patterns) of detected objects and comparing them against learned characteristics of sensitive objects, the system can adapt to unknown object types and maintain reliable privacy protection without relying on pre-programmed blacklists.
3Reliability
If user-defined policies are implemented for object identification, then privacy control is improved, but system complexity increases due to policy management and object identification processes
Solution Approach 1:
The system implements self-service through automated object identification and filtering based on user-defined policies. Instead of requiring manual configuration for each object type, the system automatically detects objects, identifies their characteristics, and applies appropriate filtering actions based on the policy framework. This automation reduces the operational complexity burden on users while maintaining strong privacy control.
Solution Approach 2:
The patent creates a universal filtering framework that can handle multiple object types and sensitivity levels through a single integrated system. The same infrastructure (camera, processor, database of object characteristics) serves multiple functions: detecting people, objects, animals, and other entities, and applying various filtering actions (blurring, masking, removal) based on unified privacy policies, thereby reducing overall system complexity compared to separate specialized systems.
Data Source
AI summary
Systems and methods are provided herein for only including portions of a user's environment that have been approved by a user in a video conference while excluding portions that have not been approved. This may be accomplished by a device receiving a policy identifying one or more approved objects of a scene of a video stream. The device may then generate a filtered video stream by only including portions of the scene that comprise the one or more objects that were approved by the policy in the filtered video stream. The filtered video stream may be combined with other video streams to generate a video conference that is transmitted and/or stored by one or more devices participating in the video conference.