Fringe projection has been widely used for 3D geometry measurement in several classes of applications. The basic system is formed by a fringe projector and a camera. A triangulation algorithm is frequently used for retrieving 3D information from a scene. Alternatively, two cameras can be used in combination with one fringe projector. This configuration produces a significant measurement uncertainty improvement since only phase information encoded in the fringe pattern is used to locate homologue points in the triangulation algorithm and lack of linearity or imperfections of the fringe projector does not induce measurement errors. However, some parts with complex geometry can not easily been seen from both cameras in a convenient angle, what limits the applicability of this configuration. Frequently the clouds of points acquired from such systems are non-structured and, consequently, a non-regular mesh is obtained. This paper presents a very simple and effective procedure to combine data from multiple cameras to produce clouds of points in a regular mesh. The main idea starts by setting two independent coordinates for a node of a regular mesh. The third coordinate is found by scanning the dependent coordinate across the measurement volume until the phase values of the fringe patterns, acquired for the multiple cameras, reach the same common value. That approach naturally produces structured clouds of points independently of the number of cameras used. As an example, a 3D shape is acquired by an ordinary multimedia projector and a set of four low cost webcams. A calibration is necessary to reference the four webcams into the same coordinate system. For that, a reference object, composed by a set of small spheres in calibrated positions, is used.© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.