UAV Window Detection and Privacy Masking
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Solution Overview
Problem
Current uncrewed aerial vehicle (UAV) systems lack effective methods to ensure privacy by preventing image capture of windows in shared environments, which is essential for maintaining security and respecting individual privacy in residential, commercial, and educational areas.
Innovation Solution
The system employs imaging sensors on UAVs to detect windows within their field of view, records their locations as prohibited imaging zones, and either alters the captured images to exclude these areas or disables the sensors when windows are within the view, using a map-based approach to enforce privacy restrictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If UAV imaging sensors capture images in shared environments for surveillance purposes, then surveillance effectiveness is improved, but privacy of individuals inside windows deteriorates
Solution Approach 1:
The system extracts and identifies window regions from captured images using image processing algorithms, then removes or masks these identified regions to exclude them from the final image output. This separates the surveillance function from the privacy-intruding function by selectively removing only the problematic window portions while retaining other useful surveillance data.
Solution Approach 2:
The system applies different processing quality to different regions of the image: full-resolution capture for most areas maintains surveillance effectiveness, while window regions are selectively masked or blurred to protect privacy. This local differentiation allows the system to optimize for both surveillance and privacy concerns in different spatial zones simultaneously.
2Object-affected harmful factors
If UAV systems continuously monitor and process images to detect windows and enforce privacy restrictions, then privacy protection is improved, but system complexity and processing time deteriorate
Solution Approach 1:
The system performs preliminary window detection and identification during the image capture phase rather than as a separate post-processing step. By integrating window detection into the real-time imaging pipeline, the system prepares privacy protection measures in advance, reducing overall processing complexity and enabling faster response times.
Solution Approach 2:
The imaging sensor system performs multiple functions simultaneously: it captures surveillance images, detects window regions, and applies privacy masking all within a single integrated processing pipeline. This multi-functionality reduces the need for separate dedicated systems for each task, thereby managing complexity while maintaining comprehensive privacy protection.
3Object-affected harmful factors
If UAVs alter or disable imaging sensors to exclude window areas from capture, then privacy compliance is improved, but surveillance coverage and data quality deteriorate
Solution Approach 1:
Instead of disabling the entire imaging sensor or altering its physical configuration, the system extracts and masks only the specific window portions from the captured images. This selective extraction approach maintains full sensor functionality and preserves maximum surveillance data quality while removing only the privacy-intruding elements.
Solution Approach 2:
The system applies privacy protection locally to window regions rather than globally to the entire image or sensor output. This localized approach ensures that surveillance data quality remains high in all non-window areas while privacy compliance is achieved specifically where needed, minimizing overall information loss.
Data Source
AI summary
A processing system including at least one processor may capture at least one image via at least one imaging sensor of an uncrewed aerial vehicle in a shared environment, detect a window within the at least one image, determine a location of the window in the shared environment, based upon a position of the uncrewed aerial vehicle and a distance between the uncrewed aerial vehicle and at least a portion of the window that is calculated from the at least one image, and record the location of the window in a map of the shared environment as a prohibited imaging zone.