AR Projection Pixel Mapping for External Projector Calibration
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Solution Overview
Problem
Existing augmented reality technologies face challenges in accurately projecting visual content onto real-world scenes without requiring expensive hardware, rigorous setup procedures, or manual alignment, especially when dealing with unknown optical characteristics and positions of external projectors.
Innovation Solution
A method that involves serving setup frames to an external projector, recording scan images and a baseline image using a peripheral control module with a camera, calculating a pixel correspondence map, transforming the baseline image into a corrected color image from the projector's perspective, and rendering augmented reality frames for projection onto specific surfaces in the scene, allowing for high-resolution and high-accuracy alignment of visual assets with minimal setup time and effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing augmented reality technologies are used to project visual content onto real-world scenes, then visual content can be displayed, but accurate projection requires expensive hardware, rigorous setup procedures, and manual alignment
Solution Approach 1:
The patent creates a digital copy (pixel correspondence map) of the projector's optical characteristics and scene geometry through automated camera-based scanning. This digital model replaces the need for expensive specialized projection hardware, allowing standard projectors and cameras to achieve accurate augmented reality projection through software-based calibration and correction.
Solution Approach 2:
The system performs self-calibration by automatically capturing scan images, computing the pixel correspondence map, and determining the corrected color image without requiring manual alignment procedures. The automated process eliminates the need for rigorous setup procedures and manual intervention, making the system easy to deploy while maintaining high projection accuracy.
2Manufacturing precision
If existing augmented reality technologies are used, then visual content can be projected, but accurate alignment requires rigorous setup procedures and manual alignment
Solution Approach 1:
The patent performs preliminary automated calibration by capturing scan images and computing the pixel correspondence map before projection begins. This pre-computed digital model of the scene and projector characteristics enables accurate alignment to be achieved automatically, eliminating the need for time-consuming manual alignment procedures during deployment.
Solution Approach 2:
The system automatically performs alignment by computing the corrected color image based on the pixel correspondence map and scan images without requiring manual intervention. This self-aligning capability dramatically reduces setup time while maintaining high alignment accuracy between virtual and real-world elements.
3Adaptability or versatility
If external projectors with unknown optical characteristics and positions are used, then flexible deployment is possible, but accurate projection becomes difficult to achieve
Solution Approach 1:
The patent creates a comprehensive digital copy of the external projector's optical characteristics, position, and scene geometry through automated scanning and pixel correspondence mapping. This digital model captures all unknown parameters of the external projector, enabling accurate projection and alignment even when the projector's specifications and position are initially unknown, thus maintaining deployment flexibility.
Solution Approach 2:
The system uses scan images captured by the camera as feedback to compute the pixel correspondence map and determine the corrected color image. This feedback loop automatically adapts to the external projector's specific optical characteristics and position, enabling accurate projection without requiring prior knowledge of the projector's parameters, thereby supporting flexible deployment with unknown equipment.
Data Source
AI summary
One variation of method includes: serving setup frames to a projector facing a scene; at a peripheral control module comprising a camera facing the scene, recording a set of images during projection of corresponding setup frames onto the scene by the projector and a baseline image depicting the scene in the field of view of the camera; calculating a pixel correspondence map based on the set of images and the setup frames; transforming the baseline image into a corrected color image—depicting the scene in the field of view of the camera—based on the pixel correspondence map; linking visual assets to discrete regions in the corrected color image; generating augmented reality frames depicting the visual assets aligned with these discrete regions; and serving the augmented reality frames to the projector to cast depictions of the visual assets onto surfaces, in the scene, corresponding to these discrete regions.