3D Camera Twin Rendering for Surface Reconstruction and Object Positioning
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Solution Overview
Problem
Existing 3D imaging technologies face challenges in accurately reconstructing surface textures and positioning 3D objects due to limitations in spectral range, motion blur, and the need for precise calibration, particularly in AR/VR systems and metaverse applications.
Innovation Solution
A method and system utilizing a physical-based rendering technique with a digital twin of the physical camera, incorporating wave optics and a detailed camera model to minimize the dissimilarity norm between captured and rendered images, optimizing surface properties and positions of 3D objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mechanical scanning or structured lighting is used for 3D object digitization, then 3D model construction is achieved, but surface texture reconstruction accuracy and object positioning precision are insufficient
Solution Approach 1:
The patent creates a digital twin of the physical camera that replicates all optical characteristics including aberrations, diffraction patterns, and sensor responses. This digital copy enables photorealistic rendering without requiring complex physical scanning setups, resolving the contradiction by using a simplified digital model instead of complex physical scanning systems while maintaining high measurement precision
Solution Approach 2:
The invention transforms the approach by changing parameters from physical scanning measurements to digital rendering parameters. By adjusting rendering parameters in the digital twin to match captured image characteristics, the system achieves accurate surface texture reconstruction and positioning without the complexity of precise physical scanning calibration
2Measurement precision
If a Bayer filter or integrated backlight source is used in the camera, then color capture is achieved, but the spectral range is restricted limiting surface properties calibration accuracy
Solution Approach 1:
The patent introduces a spectral transformation intermediary that converts measurements from the limited Bayer filter spectral range into accurate surface properties. The digital twin model learns the spectral characteristics through captured images and uses this intermediary transformation to reconstruct full spectral surface properties, resolving the contradiction by adding a computational intermediary layer rather than requiring direct broad-spectral measurement
Solution Approach 2:
The invention replaces the need for complex multi-spectral physical measurement systems with a computational approach. The digital twin substitutes physical spectral diversity with algorithmic spectral reconstruction, using the captured images and rendering model to infer surface properties across the full spectral range without requiring physical access to multiple wavelengths
3Area of stationary object
If the scanner moves while scanning to capture different views, then complete 3D coverage is achieved, but motion blur reduces image resolution
Solution Approach 1:
The patent inverts the traditional scanning approach by instead moving the virtual camera through the digital twin scene while keeping the physical camera stationary. This generates multiple views through computational rendering rather than physical movement, eliminating motion blur while achieving complete 3D scene coverage through the virtual exploration of the digital twin
4Area of stationary object
If multiple captured images from different camera positions are used, then complete 3D object coverage is achieved, but positioning accuracy of digitized objects deteriorates
Solution Approach 1:
The patent creates a single comprehensive digital twin that incorporates all spatial and geometric information from multiple views. Instead of trying to position objects from multiple independent captured images, the system builds one accurate digital replica that contains complete 3D coverage information, eliminating positioning errors that would arise from merging multiple image-based measurements
Data Source
AI summary
A method for generating a virtual scene comprising one or more 3D objects is provided. The method includes creating a 3D model of a real world 3D scene, capturing an image of the real world 3D scene by a physical camera to obtain a captured image, creating a digital camera model of the physical camera, rendering a virtual 3D scene comprising virtual 3D objects based on the digital camera model using physical-based rendering software to obtain a virtual image, and minimizing dissimilarity norm between the captured image and the virtual image to optimize positions and surface parameters of the virtual 3D objects in the virtual 3D scene.