Video Surveillance System for Privacy Protection via Object Segmentation
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Solution Overview
Problem
Existing video surveillance systems fail to effectively prevent the exposure of uninteresting objects in captured videos by IP cameras, potentially leading to the disclosure of personal information.
Innovation Solution
A video surveillance system that includes a video receiver, a video request receiver, a camera searcher, a video processor, and a video provider, which processes videos from IP cameras to make uninteresting objects indistinguishable by detecting the object of interest and applying pixelation or blurring techniques to exclude them from the video feed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video surveillance systems capture and transmit videos from IP cameras, then monitoring capability is improved, but personal information of uninteresting objects may be exposed
Solution Approach 1:
The system extracts and identifies objects of interest from video frames using object detection algorithms. Once identified, these objects are separated from the rest of the video content through selective processing, allowing the system to preserve monitoring capability while removing potentially harmful personal information from uninteresting objects.
Solution Approach 2:
The system applies different processing qualities to different regions of the video. Objects of interest are processed with high quality to maintain monitoring effectiveness, while uninteresting objects are processed with degradation (pixelation or blurring) to protect personal information. This local differentiation resolves the contradiction between monitoring reliability and privacy protection.
2Object-affected harmful factors
If the system processes videos to make uninteresting objects indistinguishable, then privacy protection is improved, but video processing complexity increases
Solution Approach 1:
The system performs object detection and classification before video processing. By identifying objects of interest in advance, the system can apply appropriate processing (preservation or degradation) during the video processing stage, avoiding the need for complex real-time analysis and simplifying the overall processing pipeline.
Solution Approach 2:
The system introduces an object detection and classification module as an intermediary between video capture and video processing. This intermediary component automatically identifies and tags objects of interest, enabling the video processing module to apply simple rule-based processing (preserve or degrade based on tags) rather than requiring complex judgment logic.
3Measurement precision
If the system preserves all objects in video clearly, then object identification accuracy is improved, but privacy protection deteriorates
Solution Approach 1:
The system segments the video content into distinct object regions using object detection. Each detected object is classified as either 'object of interest' or 'uninteresting object'. This segmentation enables differential processing where identification accuracy is maintained for interesting objects while privacy protection is applied to uninteresting objects, resolving the contradiction between identification accuracy and privacy protection.
Data Source
AI summary
The present invention discloses a video surveillance system for preventing exposure of uninteresting objects, which is achieved by making the uninteresting objects, excluding an object of interest, in a video captured by an IP camera indistinguishable, so that their personal information may be protected.