Augmented Reality Occluded Edge Smoothing via Depth Buffer Segmentation
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Solution Overview
Problem
Existing augmented reality systems face issues with poor virtual-real occluded edge quality due to insufficient precision and resolution of depth cameras, leading to incorrect depth buffer calculations and unnatural occlusion effects.
Innovation Solution
A method that involves setting multiple virtual planes to extract occluded regions, performing depth buffer calculations, and generating an occluded image by inserting a virtual object, which improves occluded edge quality by in-painting uneven edges using 3D point information and computer vision techniques, without distorting the image or altering depth data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If depth buffer computation is performed directly according to the viewing angle, then the computation is easy and can be easily implemented by hardware, but the occluded edge quality deteriorates due to insufficient precision and resolution of the depth camera
Solution Approach 1:
The patent divides the occlusion rendering process into multiple stages: (1) perform depth buffer computation using the original low-resolution depth map to obtain preliminary occlusion regions, (2) extract edge information from these regions, (3) upscale the edge information to high resolution, and (4) re-render the occlusion using the upsampled edges. This segmentation allows the system to benefit from both the computational efficiency of direct depth buffer computation and the visual quality of high-resolution edges.
Solution Approach 2:
The patent performs preliminary depth buffer computation and edge extraction at low resolution before the final high-quality rendering. By pre-identifying occlusion regions and their edges at lower computational cost, the system prepares the necessary information for subsequent high-resolution rendering, thus achieving both efficiency and quality.
2Measurement precision
If the depth camera resolution is increased to improve occluded edge quality, then the occlusion precision improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent separates the computational workload by resolution: low-resolution depth buffer computation for region identification and high-resolution edge rendering for final output. This segmentation allows precise occlusion rendering without requiring the entire rendering pipeline to operate at high resolution, thus reducing overall computational complexity.
Solution Approach 2:
The patent creates an upsampled version of the edge information from the low-resolution depth map. By copying and scaling the essential edge features rather than processing the full high-resolution depth data, the system achieves high precision occlusion edges with minimal computational overhead.
3Ease of operation
If conventional depth buffer computation is used, then the computation can be performed without sorting in advance, but incorrect depth buffer calculations occur at occluded edges due to insufficient precision
Solution Approach 1:
The patent extracts edge information from the low-resolution depth buffer result and processes this extracted information at high resolution. By taking out the critical edge components and handling them separately with higher precision, the system maintains computational simplicity while improving reliability at occluded edges.
Solution Approach 2:
The patent performs preliminary identification of occlusion regions using simple depth buffer computation, then uses this preliminary result to guide more accurate high-resolution edge processing. This two-stage approach maintains the ease of operation of conventional methods while correcting their inaccuracies at critical locations.
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 method enhances the visual presentation of augmented reality by smoothing occluded edges and achieving accurate occlusion without reducing or distorting the image, effectively addressing the limitations of existing depth camera technology.
Implementation Method 1
a sensor reads the reflected light, and a chip performs decoding and calculating to generate an image having depth information
Data Source
AI summary
A method of improving occluded edge quality in an augmented reality system includes a data input step of using a camera set to capture a scene and an object set in the scene to obtain an original image; an occluded region extracting step of obtaining an extracted image by performing a difference operation according to a first image and a second image, which are obtained according to depth buffer calculations according to first and second virtual planes set in the scene; and an occluded image generating step of inserting a virtual object into the original image according to the extracted image, the original image and a third virtual plane, which is set between the first and second virtual planes, to obtain an occluded image with a smoothened occluded edge.