Structured Light Depth Sensing with Unfiltered Stereo Cameras
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Solution Overview
Problem
Existing depth sensing systems in artificial reality are expensive and cumbersome, making them unsuitable for lightweight applications, and unfiltered cameras struggle to distinguish structured light from ambient light, leading to inaccurate depth computations.
Innovation Solution
Implementing a depth sensing setup with a projector and two detectors, using structured light and unfiltered stereo cameras within a head-mounted display for inside-outside position tracking, object detection, and recognition, and employing triangulation techniques to differentiate structured light from ambient light by comparing depth values from overlapping camera views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If unfiltered stereo cameras are used for detecting structured light, then power demand is limited and real estate is saved, but the ability to distinguish structured light from ambient light deteriorates
Solution Approach 1:
The patent introduces structured light patterns as an intermediary signal that carries depth information. By projecting known light patterns and detecting their distortions, the system creates a mediator between the camera and the depth measurement process, enabling accurate depth sensing without requiring specialized filtered detectors.
Solution Approach 2:
The patent replaces the traditional mechanical/optical filtering approach with a computational approach. Instead of using physical filters to separate structured light from ambient light, the system uses software algorithms that analyze the temporal and spatial characteristics of light patterns to distinguish and measure depth.
2Measurement precision
If traditional depth sensing systems are used, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes the stereo cameras multi-functional by enabling them to perform both their original function of capturing environmental images and the additional function of detecting structured light for depth sensing. This eliminates the need for separate dedicated depth sensing hardware while maintaining measurement precision.
Solution Approach 2:
The patent changes the detection parameters by analyzing the temporal variations and spatial patterns of light reflections. By measuring how structured light patterns distort on object surfaces and comparing them across multiple camera views, the system computes depth information using standard camera hardware with modified processing parameters.
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 solution enables accurate and efficient depth sensing in artificial reality systems, reducing costs and complexity while improving the ability to distinguish structured light from ambient light, thus enhancing the precision of depth computations.
Implementation Method 1
the detector detects emitted light reflected off of objects in the environment
Data Source
AI summary
In one embodiment, a computing system may access a first image and a second image of at least a common portion of an environment while a light emission with a predetermined emission pattern is projected by a projector. The first and second images are respectively captured by a first and a second detector that are respectively separated from the projector by a first and a second distance. The system may determine that a first portion of the first image corresponds to a second portion of the second image. The system may compute, using triangulation, a first depth value associated with the first portion and a second depth value associated with the second portion. The system may determine that the first and second depth values match in accordance with one or more predetermined criteria, and generate a depth map of the environment based on at least one of the depth values.