3D Mirror Reconstruction via Polarization Field Triangulation
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Solution Overview
Problem
Existing methods for reconstructing mirror surfaces are inadequate due to their 'invisible' nature, as they rely on insufficient ray path information and require additional geometry constraints, making it difficult to accurately recover 3-D geometry, especially for complex shapes.
Innovation Solution
A system and method utilizing a polarization field generated by a commercial LCD without a top polarizer, where each outgoing ray has a unique polarization state, allowing for the decoding of incident rays and their directions, enabling accurate 3-D reconstruction of mirror surfaces through ray-ray triangulation and Poisson integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple viewpoints or moving illuminant are used to determine ray direction, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent changes the polarization state parameter of the light source to encode ray direction information. By using a polarization field with unique polarization states for different ray directions, the system determines ray paths without requiring multiple viewpoints or moving illuminants, thus improving measurement precision while avoiding increased device complexity
Solution Approach 2:
The patent introduces polarization state as an intermediary carrier to encode ray direction information. The polarization field acts as a mediator between the light source and the mirror surface, allowing the system to extract directional information from the reflected light's polarization properties without complex mechanical setups
2Device complexity
If additional geometry constraints are assumed, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The patent uses polarization state as an additional parameter to encode surface geometry information. By analyzing the polarization changes of reflected light, the system can reconstruct mirror surfaces with high precision without needing to assume geometric constraints like planarity or smoothness, thus maintaining manufacturing precision while keeping device complexity low
3Measurement precision
If coded patterns are laid out on the mirror surface, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent uses the polarization field as an intermediary to encode measurement information in the light itself, rather than requiring physical patterns to be applied to the mirror surface. The polarization state of the reflected light carries the necessary information for precise surface reconstruction, eliminating the need for manual pattern application and improving ease of operation
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 effectively reconstructs complex mirror surfaces with high fidelity, eliminating the need for rotating polarizers and additional constraints, and is validated through both simulated and real-world experiments with accurate surface normal maps and 3-D surface recovery.
Implementation Method 1
A light source generates light that is received by a polarization field generator of the system. The polarization field generator generates a polarization field that illuminates the target object being imaged such that each outgoing ray has a unique polarization state.
Implementation Method 2
A camera of the system captures images of the illuminated target object
Implementation Method 3
The captured images are received by a processor of the system that: (1) performs a polarization field decoding algorithm that decodes the polarization field to obtain a set of incident rays
Implementation Method 4
performs a ray-ray triangulation to determine a set of 3-D intersection points
Implementation Method 5
performs a 3-D reconstruction algorithm that uses the set of incident rays, the set of camera rays and the intersection points to reconstruct a 3-D surface
Data Source
AI summary
A system and method are provided for reconstructing 3-D point cloud. A light source generates light that is received by a polarization field generator, which generates a polarization field that illuminates the target object being imaged such that each outgoing ray has a unique polarization state. A camera captures images of the illuminated target object and the captured images are received by a processor that: (1) performs a polarization field decoding algorithm that decodes the polarization field to obtain a set of incident rays; (2) performs a camera ray decoding algorithm to obtain a set of camera rays; (3) performs a ray-ray intersection algorithm that determines intersection points where the incident rays and the camera rays intersect; and (4) performs a 3-D reconstruction algorithm that uses the set of incident rays, the set of camera rays and the intersection points to reconstruct a 3-D point cloud of the target object.