Identity Protection in Surveillance Camera Environments
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Solution Overview
Problem
Conventional CCTV camera systems are intrusive and fail to protect individual identities effectively, as existing privacy protection algorithms are vulnerable to hacking during data streaming.
Innovation Solution
A novel technique using human pose-estimation to secure identities in CCTV camera environments, allowing for seamless protection and recovery of identities through a mechanism that masks and unmask body parts, including faces and associated objects, using a combination of edge and cloud servers for processing and encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional privacy protection algorithms are used to mask identities in CCTV footage, then identity exposure is reduced, but the protection is vulnerable to hacking during data streaming
Solution Approach 1:
The patent applies preliminary action by performing identity masking at the source (CCTV camera) before data leaves the premises. The masking is applied during video encoding/compression at the camera itself, so that only masked data is transmitted or stored. This preliminary protection ensures that even if data is intercepted during streaming, the identities remain protected because the sensitive information was already obscured before transmission.
Solution Approach 2:
The patent introduces an intermediary mechanism by using masked video data as an intermediate representation. Instead of transmitting or storing raw video containing identifiable information, the system uses masked video where identities are obscured through pixel manipulation or blurring. This intermediary masked data serves as a protective layer between the original video and any potential hackers or unauthorized access points.
2Reliability
If identity masking is applied to protect privacy, then privacy security is improved, but the ability to recover identities for security events is lost
Solution Approach 1:
The patent applies segmentation by separating the video data into different components: masked video data for privacy protection and auxiliary identity information stored separately. The masking process divides the original video into protected regions (faces, plates) and non-protected regions. This segmentation allows the system to maintain privacy while preserving the ability to recover identities when needed, as the auxiliary information is stored in a separate, secure manner.
Solution Approach 2:
The patent applies local quality by applying masking selectively only to specific regions of the video that contain identity information (such as faces and license plates), rather than masking the entire video. This allows other important details in the video to remain visible and useful for security analysis. The local application of masking preserves overall video quality and utility while protecting only the sensitive identity portions.
3Reliability
If comprehensive identity masking is applied to all persons in CCTV footage, then privacy protection is maximized, but video quality and useful information are compromised
Solution Approach 1:
The patent applies local quality by applying masking selectively only to specific regions of the video that contain identity information (such as faces and license plates), rather than masking the entire video. This allows other important details in the video to remain visible and useful for security analysis. The local application of masking preserves overall video quality and utility while protecting only the sensitive identity portions.
Solution Approach 2:
The patent applies partial action by implementing masking only where necessary (on identity-bearing regions) rather than applying it excessively across the entire video frame. This partial application maintains the optimal balance between privacy protection and video quality, ensuring that the video remains useful for security purposes while adequately protecting individual identities.
Data Source
AI summary
A mechanism is described for facilitating protection and recovery of identities in surveillance camera environments according to one embodiment. An apparatus of embodiments, as described herein, includes detection and reception logic to receive a video stream of a scene as captured by a camera, wherein the scene includes persons. The apparatus may further include recognition and application logic to recognize an abnormal activity and one or more persons associated with the abnormal activity in a video frame of the video stream. The apparatus may further include identity recovery logic to recover one or more identities of the one or more persons in response to the abnormal activity, where the one or more identities are recovered from masked data and encrypted residuals associated with the one or more persons.