KEYWORDS: Projection systems, Cameras, Calibration, Fringe analysis, Image processing, Camera calibration, 3D projection, 3D modeling, 3D image processing
Metric three-dimensional reconstruction by fringe projection profilometry requires calibrating the employed camera and projector. However, the calibration process is more difficult for projectors than for cameras. This work presents a reconstruction method where the projector parameters are not required explicitly. For this, we assume the projector follows the pinhole model and single-axis fringe projection is employed. The theoretical principles are explained, and the proposed method is validated experimentally by a metric three-dimensional reconstruction. The results provide a theoretical framework for further generalization, including implicit camera calibration and lens distortion, while keeping the metric reconstruction capability.
Fourier Transform Profilometry (FTP) is a powerful 3D reconstruction method based on structured-light projection suitable for dynamic shape measurements. A main feature of FTP is that it works using a single fringe pattern. However, the quality of the 3D reconstruction largely depends on the accuracy of first-order spectrum filtering. This work compares some representative spectrum filtering methods in different simulated situations, highlighting advantages and drawbacks. This study provides a reference for the practical implementation of a FTP system.
Vision systems have become a promising feedback sensor for robot navigation due to their ability to extract meaningful scene information. In this work, a multicamera system is proposed to estimate the position and orientation of an omnidirectional robot. For this, three calibrated devices (two smartphones and a webcam) are employed. Also, two badges of different colors are placed on the omnidirectional robot to detect its position and orientation. The obtained pose information is used as feedback for the robot trajectory controller. The results show that the proposed system is a useful alternative for the visual localization of ground mobile robots.
KEYWORDS: Cameras, Virtual reality, RGB color model, Human-machine interfaces, Coded apertures, 3D modeling, Visual process modeling, Video processing, Video, MATLAB
Modern advances in optical metrology and computer vision have provided an unprecedented ability to generate a wide variety of 3D digital content. The mouse, trackpad, and touch screens are typical 2D interactive interfaces of digital content. However, such interfaces are restrictive to manipulate 3D content such as models, object scans, and environments. In this work, a 3D pointer based on stereo vision to interact virtually with digital 3D objects is proposed. The theoretical principles and the experimental calibration procedure are provided. The proposed 3D pointer is evaluated experimentally by simple interaction routines with objects reconstructed by fringe projection profilometry.
Nowadays, computer vision is an essential part of modern autonomous mobile robots. Fisheye cameras are employed to capture large scenes with a single camera, but the hard radial distortion limits the accuracy of measurements. In this research, a vision system with multiple low-distortion cameras to capture large flat scenes from different viewpoints is proposed. This system applies a homography-based image mosaicing method and linear image interpolation. The obtained results show that the proposed system is useful for visual navigation of ground mobile robots.
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