Surveillance Video Privacy Obfuscation via Object Recognition
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Solution Overview
Problem
Video surveillance systems capture detailed interactions, raising concerns about privacy preservation as they often expose sensitive information and data, particularly in public and private settings.
Innovation Solution
The implementation of methods and systems that use object recognition and neural networks to identify privacy-sensitive regions and objects, applying obfuscation techniques such as pixel scrambling or blur-kernels to protect sensitive data during surveillance, ensuring that only non-sensitive information is visible when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video surveillance systems capture detailed interactions to improve monitoring quality, then surveillance effectiveness is improved, but privacy preservation deteriorates as sensitive information is exposed
Solution Approach 1:
The system applies different processing qualities to different regions of the video feed. Privacy-sensitive regions (such as areas showing documents, faces, or confidential information) are automatically detected and subjected to obfuscation processing, while non-sensitive regions maintain their original high quality for effective surveillance monitoring.
Solution Approach 2:
An intermediate processing layer is introduced between the video capture and output stages. This intermediary system uses machine learning models to analyze video content in real-time, identify privacy-sensitive regions, and apply selective obfuscation, thereby mediating between the need for detailed surveillance and privacy protection requirements.
2Object-affected harmful factors
If obfuscation techniques are applied to sensitive regions to preserve privacy, then privacy preservation is improved, but information visibility deteriorates in those regions
Solution Approach 1:
The system maintains high information visibility in non-sensitive regions while applying localized obfuscation only to privacy-sensitive areas. This ensures that surveillance effectiveness is preserved for general monitoring purposes while protecting specific privacy-sensitive information through region-specific processing.
Solution Approach 2:
Instead of applying full obfuscation to entire video feeds, the system applies partial obfuscation only to the extent necessary for privacy protection. Machine learning models precisely delimit sensitive regions and apply obfuscation at the minimum level required, avoiding unnecessary information loss in non-sensitive areas.
3Speed
If real-time processing is implemented to identify and obfuscate sensitive data, then privacy protection responsiveness is improved, but system complexity increases
Solution Approach 1:
The system employs self-service mechanisms where machine learning models automatically perform real-time analysis of video content, identify privacy-sensitive regions, and trigger obfuscation processing without human intervention. This automation enables rapid privacy protection response while managing system complexity through integrated AI algorithms.
Solution Approach 2:
Traditional manual or rule-based privacy protection methods are replaced with machine learning-based automated systems. These intelligent systems can rapidly analyze video content, recognize sensitive information patterns, and apply appropriate obfuscation in real-time, achieving both high responsiveness and manageable complexity through algorithmic intelligence.
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for preserving privacy in surveillance. The methods, systems, and apparatus include actions of obtaining images of a scene captured by a camera, identifying an object in the images through object recognition, determining that the object that is identified in the images is of a particular type that has a privacy restriction, and in response to determining that the object in the images is of the particular type that has the privacy restriction, obfuscating an appearance of the object in the images.