Camera-Assisted SLM Geometric Correction on Arbitrary Surfaces

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Solution Overview

Problem

Spatial light modulators (SLMs) project images on arbitrary surfaces, leading to non-linear distortions and misalignments due to the shape of the surface, which existing geometric correction methods fail to adequately address.

Innovation Solution

A camera-assisted geometric correction method using multiple SLMs to generate point clouds, determine warp maps, and apply rigid body transforms to correct distortions, ensuring accurate projection on arbitrary surfaces.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If multiple cameras and coordinate system transforms are used to correct geometric distortions, then manufacturing precision is improved, but device complexity increases

Engineering Contradiction:

Improvegeometric correction accuracyVSAvoidsystem complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

A pattern of points is projected onto the arbitrary surface and captured by multiple cameras to serve as intermediary reference markers. These points enable the establishment of coordinate system relationships between different cameras and the projection device, facilitating accurate geometric correction without requiring direct complex calibration between all components.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

Point clouds representing the arbitrary surface are generated from camera images and used as digital copies for coordinate transformation calculations. The rigid body transform operates on these copied point cloud representations rather than directly on the physical surface, simplifying the correction process while maintaining accuracy.

Inventive Principle:

Principle #26Copying

2Measurement precision

If rigid body transforms and point cloud processing are applied, then measurement precision is improved, but loss of time increases

Engineering Contradiction:

Improvecoordinate alignment accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

Point clouds are generated from camera images in advance, and coordinate system relationships are established before the actual projection and correction process. The rigid body transform parameters are calculated beforehand based on the captured point patterns, enabling faster real-time correction during operation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Physical coordinate measurement and alignment procedures are replaced with computational point cloud processing and mathematical rigid body transformations. This substitution of mechanical measurement with digital computation reduces processing time while maintaining or improving precision.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12432324B2Methods and apparatus for camera assisted geometric correction

Publication Date: 2025.09.30 TEXAS INSTRUMENTS INC

AI summary

An example apparatus includes: a controller configured to: generate a pattern of points; obtain a first image of a first reflection of a projection of the pattern of points from a first camera; generate a first point cloud having a first coordinate system based on the first image; obtain a second image of a second reflection of the projection of the pattern of points from a second camera; generate a second point cloud having a second coordinate system based on the second image; determine a rigid body transform to convert coordinates of the second coordinate system to coordinates of the first coordinate system; apply the rigid body transform to the second point cloud to generate a transformed point cloud; and generate a corrected point cloud based on the transformed point cloud.