Specular Surface Reconstruction via Spherical Coordinate Mapping
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Solution Overview
Problem
Current methods struggle to accurately measure and reconstruct the shapes of objects with specular surfaces due to their reflective characteristics, which differ from diffuse materials, making it challenging to capture and interpret reflections effectively.
Innovation Solution
A system comprising computer-readable storage media and processors that obtain encoded images, generate light-modulating-device-pixel indices, calculate surface normals, and map these to a spherical image sensor to produce spherical-coordinate representations, allowing for the reconstruction of surface coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging methods are used to capture specular surfaces, then the reflective characteristics cause measurement errors and incomplete data, but the patent employs encoded images with light-modulating devices and spherical coordinate mapping to achieve accurate reconstruction of specular objects
Solution Approach 1:
The patent introduces an intermediary encoding scheme where light-modulating devices (LCD panels) modulate light patterns before illuminating the object. This encoding process transforms the problematic specular reflections into measurable encoded patterns that can be decoded to extract accurate surface geometry, effectively using the intermediary encoding layer to bridge the gap between specular surfaces and accurate measurement
Solution Approach 2:
The patent transforms the measurement problem from conventional 2D image space to spherical coordinate space by mapping surface normals to a spherical image sensor. This dimensional transformation allows the system to capture and reconstruct specular surfaces that would be invisible or distorted in traditional Cartesian coordinate imaging, adding a new dimensional perspective to the measurement process
2Loss of information
If traditional light reflection capture methods are used, then specular surfaces produce mirror-like reflections that lose surface information, but the patent uses light-modulating devices to encode light patterns that preserve surface geometry data
Solution Approach 1:
The patent applies preliminary encoding of light patterns using light-modulating devices before the light interacts with the object surface. By pre-encoding the light with known patterns, the system ensures that even specular reflections carry encoded surface geometry information that can be decoded later, preventing information loss before the measurement process begins
Solution Approach 2:
The system employs feedback through the decoding process where captured encoded images are processed to extract surface normals and reconstruct geometry. The decoded information feeds back into the reconstruction algorithm, allowing the system to iteratively improve accuracy and compensate for information that might be lost in specular reflections
3Measurement precision
If the system processes encoded images through multiple computational steps, then measurement accuracy improves, but processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the complex reconstruction process into distinct computational modules: encoding pattern generation, image capture, decoding to extract surface normals, spherical coordinate mapping, and final geometry reconstruction. This segmentation allows each module to be optimized independently and facilitates parallel processing, reducing overall computational complexity while maintaining high measurement precision
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
Enables accurate reconstruction of object shapes by effectively handling specular reflections, providing precise surface normal calculations and point cloud generation, even with complex objects like the Stanford Bunny and horse models, with minimal error and robustness against noise.
Implementation Method 1
a highly-glossy material reflects light from a directional light source primarily in only one direction or a few directions. These reflections from a highly-glossy material are specular reflections
Data Source
AI summary
Devices, systems, and methods obtain respective spherical coordinates of points on an object, obtain respective spherical-coordinate representations of surface normals at the points on the object, and generate reconstructed surface coordinates based on the respective spherical coordinates and on the respective spherical-coordinate representations of the surface normals.