Open AccessConstraints for Time-Multiplexed Structured Light with a Hand-held Camera
Author(s) -
Sepehr Ghavam,
Matthew Post,
Mohamed A. Naiel,
Mark Lamm,
Paul Fieguth
Publication year - 2021
Publication title -
journal of computational vision and imaging systems
Language(s) - English
Resource type - Journals
ISSN - 2562-0444
DOI - 10.15353/jcvis.v6i1.3562
Subject(s) - reprojection error , homography , computer vision , pinhole camera model , artificial intelligence , camera matrix , projector , computer science , structured light , camera auto calibration , camera resectioning , pinhole camera , pixel , frame (networking) , point (geometry) , computer graphics (images) , mathematics , image (mathematics) , projective test , projective space , optics , geometry , telecommunications , statistics , physics
Multi-frame structured light in projector-camera systems affords high-density and non-contact methods of 3D surface reconstruction. However, they have strict setup constraints which can become expensive and time-consuming. Here, we investigate the conditions under which a projective homography can be used to compensate for small perturbations in pose caused by a hand-held camera. We synthesize data using a pinhole camera model and use it to determine the average 2D reprojection error per point correspondence. This error map is grouped into regions with specified upper-bounds to classify which regions produce sufficiently minimal error to be considered feasible for a structured-light projector-camera system with a hand-held camera. Empirical results demonstrate that a sub-pixel reprojection accuracy is achievable with a feasible geometric constraints