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

Fuente: arXiv
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Autori principali: Kawano, Takumi, Miura, Kohei, Iwai, Daisuke
Natura: Preprint
Pubblicazione: 2026
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author Kawano, Takumi
Miura, Kohei
Iwai, Daisuke
author_facet Kawano, Takumi
Miura, Kohei
Iwai, Daisuke
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2604_24024
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Breaking the Scalability Limit of Multi-Projector Calibration with Embedded Cameras
Kawano, Takumi
Miura, Kohei
Iwai, Daisuke
Computer Vision and Pattern Recognition
Graphics
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.
title Breaking the Scalability Limit of Multi-Projector Calibration with Embedded Cameras
topic Computer Vision and Pattern Recognition
Graphics
url https://arxiv.org/abs/2604.24024