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.

翻译：传统多投影仪标定需依次投射并采集每台投影仪的结构光图案，导致标定时间和工作量随投影仪数量线性增长。这一可扩展性瓶颈长期制约着大规模投影映射系统的部署。我们提出一种突破该限制的标定框架，通过在校准靶标表面嵌入摄像头实现突破。嵌入式摄像头可直接捕捉入射投影光，从而根据入射方向分离多台投影仪同时投射的结构光图案。该方法建立了嵌入式摄像头光学中心与投影仪像素间的对应关系，使得所有投影仪的内外参数可同步估计。我们进一步引入修正技术以消除校准板与摄像头光学中心间的微小偏移。实验表明，本系统在保持与传统方法相当的标定精度的同时，将所需投影-采集周期数从与投影仪数量呈线性关系优化为近似恒定值，显著提升了密集多投影仪系统的可扩展性，尤其适用于高亮度堆叠、超分辨率、光场及阴影抑制显示等重叠投影区域的应用场景。