Breaking the Scalability Limit of Multi-Projector Calibration with Embedded Cameras

2026-04-27

AI Summary

This work addresses the scalability limitation of conventional multi-projector calibration, which requires sequential projection of structured light patterns, resulting in a linear increase in calibration time with the number of projectors. To overcome this, the authors propose an embedded-camera calibration method that integrates an array of cameras into the calibration target to simultaneously capture structured light patterns from all projectors. By leveraging the direction of incident rays to disentangle overlapping patterns, the method establishes correspondences between the optical centers of the embedded cameras and projector pixels, enabling joint estimation of intrinsic and extrinsic parameters. This approach achieves, for the first time, synchronous multi-projector calibration using embedded cameras, reducing the projection–capture cycle from linear to nearly constant time. It maintains accuracy comparable to traditional methods while significantly improving calibration efficiency for large-scale, densely packed projector systems, with direct applicability to high-brightness blending, super-resolution, light-field displays, and shadow suppression.

Technology Category

• Computer Vision: Multi-modal Vision
• Machine Learning: Calibration & Uncertainty Quantification
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Conventional multi-projector calibration requires projecting and capturing structured light patterns for each projector sequentially, causing calibration time and effort to increase linearly with the number of projectors. This scalability bottleneck has long limited the deployment of large-scale projection mapping systems. We present a new calibration framework that breaks this limitation by embedding cameras into the surface of the calibration target. The embedded cameras directly capture the incoming projection light, enabling the separation of simultaneously projected structured light patterns from multiple projectors according to their incident directions. Our method establishes correspondences between the optical centers of the embedded cameras and the projector pixels, allowing the intrinsic and extrinsic parameters of all projectors to be simultaneously estimated. We further introduce a correction technique for small misalignments between the calibration board and camera optical centers. As a result, our system achieves calibration accuracy comparable to conventional methods while reducing the required number of projection-capture cycles from linear to nearly constant with respect to the number of projectors, dramatically improving scalability for dense multi-projector systems with overlapping projection regions, such as high-brightness stacking, super-resolution, light-field, and shadow-suppression displays.

Problem

• multi-projector calibration
• scalability
• structured light
• projection mapping
• calibration time

Innovation

• multi-projector calibration
• embedded cameras
• structured light
• scalability
• simultaneous estimation