Simulated Proximity Detection Using IR Camera Brightness Analysis
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Solution Overview
Problem
Devices in augmented and mixed reality environments lack a proximity detector, necessitating a method to detect user proximity without traditional proximity sensors.
Innovation Solution
Utilizing infrared (IR) cameras to capture image data and analyze brightness statistics, determining if a proximate object is present by comparing pixel brightness values within specific ranges, thereby simulating proximity detection to power on or off device systems accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional proximity sensors are used, then proximity detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes the IR camera serve multiple functions: it performs both facial recognition and proximity detection. By utilizing the existing IR camera for proximity sensing, the system eliminates the need for separate proximity sensors, thereby reducing device complexity while maintaining detection capabilities
Solution Approach 2:
The patent creates a simulated proximity sensor by processing image data from the IR camera. Instead of using a physical proximity sensor, the system generates proximity detection information through software processing of camera images, effectively copying the functionality of a proximity sensor using existing hardware
2Device complexity
If IR cameras are used for proximity detection, then device complexity is reduced, but measurement precision may deteriorate
Solution Approach 1:
The patent divides the image data processing into specific regions of interest (face region and non-face region) and applies different brightness threshold criteria to each segment. This segmentation allows the system to accurately distinguish between a user's face and other objects, improving measurement precision while using a single IR camera
Solution Approach 2:
The patent uses different brightness threshold values for different regions (face region vs. non-face region) and adjusts these thresholds based on ambient light conditions. By dynamically changing detection parameters, the system maintains high measurement precision across varying environmental conditions while using the same IR camera hardware
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
Effectively detects user proximity using IR cameras, allowing devices to adjust operations such as powering on or off, enhancing wearable device functionality by determining when a user is wearing or not wearing the device.
Implementation Method 1
brightness statistics of image data captured by an infrared (IR) camera
Data Source
AI summary
A system for detecting a proximate object includes one or more cameras and one or more illuminators. The proximate object is detected by obtaining image data captured by the one or more cameras, where the image data is captured when at least one of the one or more illuminators are illuminated, determining brightness statistics from the image data, and determining whether the brightness statistics satisfies a predetermined threshold. The proximate object is determined to be detected in accordance with a determination that the brightness statistics satisfies the predetermined threshold.