Camera-Assisted Projection Surface Characterization and Correction
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Solution Overview
Problem
Existing projection systems face challenges in accurately projecting images onto non-planar and irregular surfaces, leading to keystone and local aspect ratio distortions that hinder the observer's ability to perceive the image correctly, as manual correction is difficult and requires complex calibration.
Innovation Solution
A camera-assisted system that projects a geometric progression of structured light elements to characterize the projection screen surface, determining its three-dimensional structure and compensating for distortions by adjusting image projections to maintain a rectangular aspect ratio, using dual-camera systems to minimize manufacturing tolerances and reduce calibration needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual correction methods are used for keystone and surface distortion, then correction capability is achieved, but device complexity and calibration difficulty increase significantly
Solution Approach 1:
The system automatically characterizes the projection screen surface and calculates compensation transformations without requiring manual calibration. The camera captures the projected pattern, the processor automatically determines surface geometry, and the system self-corrects distortions through computed transformation matrices, eliminating the need for manual intervention
Solution Approach 2:
The system changes the parameter representation from manual calibration coordinates to camera-based 3D surface characterization. By capturing images and computing 3D point clouds, the system transforms the correction approach from geometry-based manual adjustment to image-based automatic parameter determination
2Measurement precision
If structured light elements are projected for surface characterization, then measurement precision improves, but loss of time increases due to iterative projection
Solution Approach 1:
The system projects structured light patterns in a sequential, periodic manner through multiple frames. Each frame captures a different phase or pattern of the structured light, and the processor integrates information across these periodic projections to build the complete 3D surface characterization
Solution Approach 2:
The system performs preliminary surface characterization by projecting and capturing the structured light pattern before the actual image projection. This preliminary 3D mapping enables pre-computation of compensation transformations, so that when the final image is projected, the distortions are already corrected based on the pre-acquired surface data
3Ease of operation
If camera-assisted automatic characterization is implemented, then ease of operation improves, but device complexity increases due to additional hardware
Solution Approach 1:
The camera serves multiple functions: it captures the structured light pattern for surface characterization, provides calibration data for the projection system, and enables automatic distortion correction. This multi-functionality justifies the added hardware by eliminating the need for separate calibration devices and manual procedures
4Manufacturing precision
If compensation transformations are calculated based on 3D point clouds, then manufacturing precision requirements are reduced, but computation complexity increases
Solution Approach 1:
The system replaces mechanical precision requirements with computational processing. Instead of requiring precisely manufactured components and alignment mechanisms, the system uses camera-based 3D sensing and software algorithms to automatically determine and correct for any physical imperfections in the projection system and screen
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
The system effectively corrects keystone and surface distortions, ensuring a rectangular image is perceived by the observer without manual intervention, enhancing the viewing experience by accurately compensating for irregularities in the projection surface.
Implementation Method 1
A camera is triggered to capture an image of the displayed structured light elements
Data Source
AI summary
In described examples, a geometric progression of structured light elements is iteratively projected for display on a projection screen surface. The displayed progression is for determining a three-dimensional characterization of the projection screen surface. Points of the three-dimensional characterization of a projection screen surface are respaced in accordance with a spacing grid and an indication of an observer position. A compensated depth for each of the respaced points is determined in response to the three-dimensional characterization of the projection screen surface. A compensated image can be projected on the projection screen surface in response to the respaced points and respective compensated depths.