Dynamic Illumination Power Control for Depth Tracking
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Solution Overview
Problem
Depth sensing technologies in machine vision, such as time-of-flight cameras, face challenges with high power consumption due to over-illumination, leading to increased size, weight, and cost in mobile devices, as they are often set for the worst-case scenario, resulting in unnecessary power usage.
Innovation Solution
The implementation of a near-eye display system that dynamically adjusts the illumination power of the EM emitter based on contextual information like ambient light, reflectivity, and depth of the scene to avoid over-illumination and conserve power, allowing for varying illumination powers for different depth tracking targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the illumination power is set for the worst-case scenario, then the depth sensing system can operate under all conditions, but the power consumption increases and the device size, weight, and cost increase
Solution Approach 1:
The illumination power is dynamically adjusted based on real-time environmental conditions (ambient light levels, scene depth, reflectivity) rather than being fixed at a worst-case level. The system transitions from a static high-power setting to a dynamic adaptive setting that matches actual operational needs, resolving the contradiction between reliability and power consumption.
Solution Approach 2:
The system changes the illumination power parameter according to contextual information such as ambient light levels, depth of scene, and reflectivity values. By adjusting this key parameter based on environmental conditions, the system maintains reliable depth sensing while avoiding unnecessary power consumption in favorable conditions.
2Reliability
If the illumination power is set for the worst-case scenario, then the depth sensing system can handle all environmental conditions, but the device size, weight, and cost increase
Solution Approach 1:
The system dynamically adjusts illumination power based on environmental feedback, allowing the use of a smaller, lighter power source that wouldn't otherwise be sufficient for worst-case scenarios. The adaptive control compensates for the reduced power source capacity by intelligently managing power delivery based on actual conditions.
Solution Approach 2:
By changing the illumination power parameter according to contextual information, the system can use a smaller battery or power source that would be inadequate for fixed worst-case operation, thereby reducing device weight while maintaining operational reliability through adaptive power management.
3Reliability
If the illumination power is set for the worst-case scenario, then the depth sensing system can operate in all lighting conditions, but the power consumption increases unnecessarily in many cases
Solution Approach 1:
The system uses feedback from environmental sensors (ambient light levels, depth information, reflectivity measurements) to adjust illumination power in real-time. This closed-loop control prevents energy waste by matching illumination output to actual environmental conditions while ensuring reliable operation when needed.
Solution Approach 2:
The illumination power parameter is continuously adjusted based on contextual feedback, allowing the system to operate efficiently in favorable conditions (reducing energy waste) while maintaining the capability to handle worst-case scenarios when environmental conditions deteriorate.
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
This approach reduces power consumption in depth tracking operations by optimizing illumination power according to contextual conditions, thereby minimizing the power source requirements and enhancing the efficiency of depth sensing systems in mobile devices.
Implementation Method 1
A ToF camera has a light source to emit light onto nearby objects. Light reflected off surfaces of the objects can be captured by the ToF camera.
Implementation Method 2
The time it takes for the light to travel from the light source of the ToF camera and reflect back from an object is converted into a depth measurement
Implementation Method 3
Emitting light at one or more known frequencies and comparing the phase of received reflected light with that of the emitted light enables a calculated phase delay. Knowing one or more phase delays of the reflected light enables a processor to determine the distance to the object
Data Source
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AI summary
An illumination module and a depth camera on a near-eye-display (NED) device used for depth tracking may be subject to strict power consumption budgets. To reduce power consumption of depth tracking, the illumination power of the illumination module is controllably varied. Such variation entails using a previous frame, or previously recorded data, to inform the illumination power used to generate a current frame. Once the NED determines the next minimum illumination power, the illumination module activates at that power level. The illumination module emits electromagnetic (EM) radiation (e.g. IR light), the EM radiation reflects off surfaces in the scene, and the reflected light is captured by the depth camera. The method repeats for subsequent frames, using contextual information from each of the previous frames to dynamically control the illumination power. Thus, the method reduces the overall power consumption of the depth camera assembly of the NED to a minimum level.