Privacy Processor Video Fidelity Adjustment
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Solution Overview
Problem
Surveillance systems face challenges in balancing security with privacy concerns, particularly in residential settings where personnel at central monitoring stations may have access to video footage, raising concerns about unauthorized use of personal data.
Innovation Solution
The system employs privacy processors that dynamically adjust video data fidelity based on social context, using identification and face recognition analytics to ensure authorized users' privacy by blurring or masking images of recognized individuals, while maintaining full recording and alert capabilities when the area is unoccupied.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video surveillance is implemented to detect threats and monitor secured areas, then security and threat detection capability are improved, but privacy of occupants is compromised due to access to video footage by central monitoring personnel
Solution Approach 1:
The system applies different processing quality levels to different portions of the video feed. Full-resolution video is maintained for threat detection purposes, while selective blurring or masking is applied to areas containing personal information or private activities. This allows the system to maintain security monitoring capability while protecting privacy in specific local regions of the video feed.
Solution Approach 2:
The video feed is segmented into different regions of interest, with independent processing applied to each segment. Critical areas for security monitoring are kept clear, while segments containing personal information are selectively obscured. This segmentation allows simultaneous achievement of security monitoring and privacy protection for different portions of the same video stream.
2Measurement precision
If full-resolution video is transmitted to central monitoring station for accurate threat detection, then detection precision is improved, but data transmission volume and processing load increase
Solution Approach 1:
The system dynamically changes video quality parameters based on detected events and contextual information. During normal conditions, video quality is reduced to minimize data transmission. When threats are detected or suspicious activities occur, the system automatically increases video quality and resolution for those specific segments, ensuring detection precision is maintained when needed while reducing overall data volume.
Solution Approach 2:
Instead of transmitting full-resolution video continuously, the system applies partial action by transmitting reduced-quality video most of the time and only escalating to full-resolution transmission when specific events trigger the need for higher quality. This approach maintains detection precision for critical events while significantly reducing overall data volume and processing requirements.
3Object-affected harmful factors
If video quality is reduced to protect privacy and reduce data transmission, then privacy protection and bandwidth usage are improved, but threat detection capability deteriorates
Solution Approach 1:
The system dynamically adjusts video quality in real-time based on detected events, contextual information, and privacy requirements. Video quality is not static but changes continuously according to the situation - maintaining high quality for threat detection while reducing quality for privacy protection when no threats are present. This dynamic adaptation ensures threat detection capability is preserved when needed while privacy protection is enhanced during normal operations.
Solution Approach 2:
The system introduces an intermediary processing layer between video capture and transmission that selectively modifies video quality. This intermediary applies intelligent algorithms to identify and protect privacy-sensitive regions while maintaining detection quality in security-critical areas. The intermediary acts as a mediator that balances the conflicting requirements of privacy protection and threat detection by applying different quality levels to different portions of the video stream.
Data Source
Figure 1
AI summary
A method and apparatus incorporating a security camera of a security system within a residence capturing a sequence of images of a secured area of the residence, a programmed processor of the security system determining that an authorized person is present within the residence, a programmed processor detecting a person within the sequence of images and a programmed processor blurring or reducing a picture quality of an area immediately around the detected person based upon the presence of the authorized person.