Display Surveillance Detection Using Two-Stage Camera Analysis
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Solution Overview
Problem
Electronic devices face privacy and security issues due to surveillance of display screens by individuals or recording devices, compromising the security and privacy of users, especially during activities like video conferencing.
Innovation Solution
The electronic device employs a camera with computer vision capabilities to detect surveillance using a two-stage approach: a scene change detector identifies potential surveillance through low-resolution image analysis, followed by a machine-learning model for high-resolution surveillance detection, generating alerts or obscuring the display to protect user data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution image processing is used for surveillance detection, then detection accuracy is improved, but energy consumption increases
Solution Approach 1:
The surveillance detection process is divided into two stages: first, low-resolution image processing to detect scene changes and identify regions of interest; second, high-resolution image processing only for the identified suspicious regions. This segmentation allows the system to maintain high detection accuracy while significantly reducing overall energy consumption by limiting intensive processing to only necessary areas.
Solution Approach 2:
The system applies different processing qualities to different regions of the image. Low-resolution processing is applied to the entire image for initial scanning, while high-resolution processing is applied locally only to regions where surveillance is suspected. This local quality approach ensures accurate detection where needed while conserving energy in other areas.
2Reliability
If continuous high-resolution monitoring is implemented, then surveillance detection reliability is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic surveillance detection using low-resolution images to monitor for scene changes, and only activates high-resolution processing when changes are detected. This periodic action pattern maintains reliable surveillance coverage while dramatically reducing energy consumption compared to continuous high-resolution monitoring.
Solution Approach 2:
The system performs preliminary low-resolution image processing to identify potential surveillance activities before committing to energy-intensive high-resolution analysis. This preliminary action filters out false positives and ensures that high-resolution processing is only triggered when truly necessary, maintaining reliability while conserving energy.
Data Source
AI summary
Examples of electronic devices are described herein. In some examples, an electronic device includes a camera. In some examples, the electronic device includes a display device. In some examples, the electronic device includes a processor to detect a scene change in a first set of images captured by the camera. The first set of images has a first resolution. The processor is also to detect surveillance of the display device in response to detecting the scene change. The surveillance detection is based on a second set of images captured by the camera. The second set of images has a second resolution that is higher than the first resolution.