Image Sensor Neural Network Privacy Obfuscation
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Solution Overview
Problem
There is a risk to individuals' privacy when images capturing their faces or vehicle license plates are recorded without permission, even if the footage is later erased, due to potential data security breaches, and existing technologies do not effectively balance the need for image capture with privacy protection.
Innovation Solution
An image sensor device equipped with two neural networks that detect regions of interest and determine if a predetermined event has occurred, obscuring sensitive areas in images when necessary to protect privacy, while allowing unobscured capture when the event is lawfully relevant, such as during video surveillance of unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If images are captured to record areas around private property for surveillance purposes, then security monitoring capability is improved, but privacy of individuals is compromised
Solution Approach 1:
The patent applies local quality by differentiating treatment of different regions within the image. Regions of interest containing identifying information (faces, license plates) are selectively obscured while other regions remain clear. This allows security monitoring of the overall scene while protecting个人隐私 of individuals, resolving the contradiction between surveillance effectiveness and privacy protection.
Solution Approach 2:
The patent implements preliminary action by proactively obscuring identifying information in regions of interest before the image is stored or transmitted. The neural network detects and marks these regions in advance, ensuring privacy protection is built into the capture process itself rather than applied as a post-processing measure. This prevents potential privacy breaches while maintaining security monitoring capability.
2Object-affected harmful factors
If identifying information is obscured in captured images, then privacy protection is improved, but ability to identify individuals when needed deteriorates
Solution Approach 1:
The patent applies dynamics by making the obscuration state conditional and changeable. The neural network dynamically determines whether to obscure regions of interest based on detected events or conditions. When a predetermined event occurs (such as detected unlawful behavior), the system can reveal identifying information; otherwise, privacy is protected. This dynamic approach resolves the contradiction by allowing identification capability to be activated only when necessary.
Solution Approach 2:
The patent implements feedback through the neural network that continuously analyzes image content and adjusts obscuration accordingly. The system monitors for predetermined events or conditions and provides feedback that controls the obscuration state. This feedback mechanism ensures identifying information is obscured during normal operation but can be revealed when security concerns arise, balancing privacy protection with identification capability.
Data Source
AI summary
An image sensor device includes circuitry configured to: receive an image; run a first neural network configured to detect one or more regions of interest in the image; and run a second neural network configured to determine, based on the image, whether a predetermined event has occurred; wherein when it is determined that the predetermined event has occurred, the image is output; and the circuitry is further configured such that the first neural network initiates obscuring processing to produce an obscured image in which the one or more regions of interest are obscured and the circuitry is configured to output the obscured image when it is determined that the predetermined event has not occurred.