ISMAR 2018
IEEEIEEE computer societyIEEE vgtcACM In-CooperationACM In-Cooperation

Sponsors

Platinum Apple
Silver MozillaIntelDaqriPTCAmazon
Bronze FacebookQualcommUmajinDisney ResearchUniSA VenturesReflektOccipital
SME EnvisageARKhronos
Academic TUMETHZ

Philipp Kurth, Vanessa Lange, Christian Siegl, Marc Stamminger, and Frank Bauer. Auto-calibration for dynamic multi-projection mapping on arbitrary surfaces. IEEE Transactions on Visualization and Computer Graphics (To appear), 2018.
[BibTeX▼]

Abstract

The quality of every dynamic multi-projection mapping system is limited by the quality of the projector to tracking device calibration. Common problems with poor calibration result in noticeable artifacts for the user, such as ghosting and seams. In this work we introduce a new, fully automated calibration algorithm that is tailored to reduce these artifacts, based on consumer-grade hardware. We achieve this goal by repurposing a structured-light scanning setup. A structured-light scanner can generate 3D geometry based on a known intrinsic and extrinsic calibration of its components (projector and RGB camera). We revert this process by providing the resulting 3D model to determine the intrinsic and extrinsic parameters of our setup (including those of a variety of tracking systems). Our system matches features and solves for all parameters in a single pass while respecting the lower quality of our sensory input.