Active Unauthorized Viewing Protection via LIDAR Detection
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Solution Overview
Problem
Existing methods for protecting visual information from unwanted viewing, such as privacy filters and holographic masking, are inadequate against small hidden cameras and provide limited protection against observant third parties, especially in environments like museums or vehicles, and are often costly and inefficiently managed by human personnel.
Innovation Solution
A method using lidar or camera-based image analysis to detect unauthorized viewers or image-recording devices within a predefined surveillance area, triggering actions like opacifying electrochromic glazing or masking content to prevent viewing, leveraging existing camera and computing hardware in devices like laptops or tablets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If privacy filters or holographic masking surfaces are used to limit viewing angle, then viewing confidentiality is improved, but protection against hidden cameras and observant third parties deteriorates
Solution Approach 1:
The patent replaces passive mechanical privacy filters with an active detection system using cameras and image processing algorithms. The system automatically detects hidden cameras and unauthorized viewers through image analysis, triggering dynamic responses such as content masking or alerts, thereby substituting static mechanical protection with intelligent automated detection and response mechanisms.
2Reliability
If human personnel are deployed to monitor and prevent unauthorized viewing, then protection effectiveness is improved, but cost and operational efficiency deteriorate
Solution Approach 1:
The system enables self-service protection by automatically detecting unauthorized viewing attempts and executing protective actions without human intervention. The automated image analysis and response mechanisms eliminate the need for continuous human monitoring, allowing the system to protect itself and its content independently, thereby improving operational efficiency while maintaining protection effectiveness.
3Device complexity
If existing camera and computing hardware are leveraged for detection, then device complexity is reduced, but detection precision and reliability may deteriorate
Solution Approach 1:
The system performs preliminary analysis of image data using advanced algorithms to identify characteristics of hidden cameras and unauthorized viewers before making detection decisions. By pre-processing and analyzing image patterns, the system enhances detection precision using existing hardware, preparing detection criteria in advance to maximize accuracy without requiring additional specialized equipment.
Data Source
AI summary
Method for automatically protecting an object, a person, or an item of visual information from a risk of unwanted viewing by a third party, an unauthorized person and/or an image-recording device. The method includes the steps of: automatically detecting, by analyzing images from at least one Light Detection and Ranging (LIDAR) or from a camera arranged so as to cover a predefined surveillance area, the presence of a third party or of an unauthorized person and/or of the device in this area or nearby, the predefined surveillance area corresponding at least to an area from which the person or the device is capable of viewing the object, the person or the information, and in the event of positive detection, triggering a predefined action.