Desenvolvimento e análise de um digitalizador câmera-projetor de alta definição para captura de geometria e fotometria

Abstract

A camera-projector system is capable of capturing three-dimensional geometric information of objects and real-world environments. The capture of geometry in such system is based on the projection of structured light over an object by the projector, and the capture of the modulated scene through the camera. With a calibrated system, the deformation of the projected light caused by the object provides the information needed to reconstruct its geometry through triangulation. The present work describes the development of a high definition camera-projector system (with resolutions up to 1920x1080 and 1280x720). The steps and processes that lead to the reconstruction of geometry, such as camera-projector calibration, color calibration, image processing and triangulation, are detailed. The developed scanner uses the (b; s)-BCSL structured light coding, which employs the projection of a sequence of colored vertical stripes on the scene. This coding scheme offers a flexible number of stripes for projection: the higher the number of stripes, more detailed is the captured geometry. One of the objectives of this work is to estimate the limit number of (b; s)-BCSL stripes possible within the current resolutions of high definition video. This limit number is the one that provides dense geometry reconstruction, and at the same has low error. To evaluate the geometry reconstructed by the scanner for a different number of stripes, we propose a protocol for error measurement. The developed protocol uses planes as objects to measure the quality of geometric reconstruction. From the point cloud generated by the scanner, the equation for the same plane is estimated by least squares. For a fixed number of stripes, five independent scans are made for the plane: each scan leads to one equation; the median plane, estimated from the union of the five clouds of points, is also computed. A distance metric in the projective space is used to evaluate the precision and the accuracy of each number of projected stripes. In addition to the quantitative evaluation, the geometry of many objects are presented for qualitative evaluation. The results show that the limit number of stripes for high resolution video allows high density of points even on surfaces with high color variation.