Model and Algorithms for Point Cloud Construction Using Digital Projection Patterns

Abstract

This paper describes a computational framework for constructing point clouds using digital projection patterns. The basic principle behind the approach is to project known patterns on the object using a digital projector. A digital camera is then used to take images of the object with the known projection patterns imposed on it. Due to the presence of 3-D faces of the object, the projection patterns appear distorted in the images. The images are analyzed to construct the 3-D point cloud that is capable of introducing the observed distortions in the images. The approach described in this paper presents three advances over the previously developed approaches. First, it is capable of working with the projection patterns that have variable fringe widths and curved fringes and hence can provide improved accuracy. Second, our algorithm minimizes the number of images needed for creating the 3-D point cloud. Finally, we use a hybrid approach that uses a combination of reference plane images and estimated system parameters to construct the point cloud. This approach provides good run-time computational performance and simplifies the system calibration. *

A robust automated markerless registration framework for neurosurgery navigation

“…Tao et al . provided a new method to calculate 3D points. In their method, the object point is calculated by the intersection of two lines emanating from the camera centre and projector centre.…”

DLP-based 3D metrology by structured light or projected fringe technology for life sciences and industrial metrology

“…By exploiting intensity gradients, triangulation is made independent of the actual pixel raster and distances can be measured at very high resolution. Supplying significant gradients for all parts of the measured surface, requires several phase shifted cos 2 intensity patterns to be projected in sequence, or, in another variety, simultaneously in different colors that can be separated by color cameras and filtering [3] . Using many parallel stripes obviously necessitates a means of identifying the individual stripe being seen.…”

Some practical considerations in fringe projection profilometry

“…Despite that numerous FPP-based 3D shape measurement approaches have been developed in the past two decades [1][2][3][4][5][6][7][8][9][10][11], the literature survey conducted by the authors reveals that some important issues have not been well addressed in the practice of FPP-based 3D shape measurements. Accordingly, this paper aims to point out a few important considerations in FPP applications, along with simple yet practical solutions that give great promise of satisfying the various high demands of enormous applications in various fields.…”