User-Facing Camera Obstruction Detection Using ALS and AE Correlation
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Solution Overview
Problem
Existing computing systems face challenges in accurately detecting user-facing camera obstructions, such as aftermarket privacy sliders, which can lead to erratic power management behavior and lack of user feedback, compromising privacy and power efficiency.
Innovation Solution
Implementing sensor fusion and correlation between ambient light sensors and user-facing camera auto-exposure to detect obstructions, providing user feedback and adjusting power management functions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor fusion and correlation between ambient light sensors and user-facing camera auto-exposure is implemented to detect obstructions, then measurement precision of camera obstruction detection is improved, but device complexity increases
Solution Approach 1:
The patent uses the auto-exposure mechanism as an intermediary indicator to detect camera obstructions. Instead of directly detecting the obstruction, the system monitors changes in auto-exposure settings required to maintain proper image brightness. When an obstruction is present, the auto-exposure adjustments needed exceed a threshold, indicating the camera is blocked. This intermediary approach improves detection accuracy without requiring complex direct sensing mechanisms.
Solution Approach 2:
The system continuously monitors auto-exposure parameters and provides feedback about obstruction status. By comparing current auto-exposure settings with historical data or threshold values, the system can detect when a camera becomes obstructed and notify the user. This feedback mechanism enables precise obstruction detection while using existing camera components, avoiding the need for additional complex sensors.
2Loss of information
If user feedback mechanisms are added to notify users of camera obstructions, then loss of information is reduced, but device complexity increases
Solution Approach 1:
The system uses the camera's own auto-exposure functionality to generate obstruction detection information, eliminating the need for separate detection hardware. The camera essentially detects its own obstruction status through its normal operation, and this self-generated information is then used to trigger user notifications. This self-service approach reduces information loss while avoiding additional complex components.
3Use of energy by moving object
If power management functions are adjusted based on obstruction detection, then use of energy is optimized, but reliability of power management behavior improves only if detection accuracy is maintained
Solution Approach 1:
The system changes power management parameters (such as camera sampling rate, processor activity, or display state) based on the detected obstruction status. When an obstruction is detected, the system can reduce power consumption by disabling or reducing activity of the obstructed camera and related processing functions. The auto-exposure parameters themselves serve as the trigger for these power management changes, creating a reliable link between detection and action without requiring additional sensors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances power management predictability and user control over camera privacy, ensuring seamless power optimization and user awareness of camera obstructions.
Implementation Method 1
an ambient light sensor value from an ambient light sensor
Implementation Method 2
a camera auto-exposure value from a user-facing camera's auto-exposure circuit
Data Source
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AI summary
There is disclosed in one example a computing apparatus, including: a main board including a processor and memory; a user-facing (UF) camera including an auto-exposure (AE) circuit; an ambient light sensor (ALS); and a power management module communicatively coupled to the UF camera and the ALS, and including logic to detect a light input mismatch between the ALS and the AE and responsive to the detection, disable a power management function of the power management module.