A comparison of new generic camera calibration with the standard parametric approach

This paper deals with a recently proposed nonparametric approach to camera calibration, which is applicable to any type of sensor design. Currently, no relative quantitative performance data is available for this method. This paper addresses this issue, by providing a comprehensive evaluation with respect to the standard planar calibration technique in the literature. Experiments are conducted on simulated and real data, with the firm conclusion that the generic calibration method has the capability to outperform the standard parametric approach for imaging systems with significant distortion. The results provide important practical information for the vision community at large

Beyond Homographies: Exploration and Analysis of Image Warping for Projection in a Dome

The goal of this project is to provide multiple approaches for warping a flat image tofit the curvature of a geodesic dome, to be presented as an immersive, Augmented Reality (AR) environment. This project looks to develop an algorithmic method of warping any image to fit perspective distortion for a dome-like surface. Despite fairly common usage in planetarium methods and other such shows, there is very little documented method that would allow for the warping of images to fit a curved projection surface. The methods will be explored include using Processing, OpenCV, and fisheye image filters. In addition to the paper, this research will also produce an online library of documents and resources for preforming these warps

Efficient lens distortion correction for decoupling in calibration of wide angle lens cameras

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In photogrammetry applications, camera parameters must be as accurate as possible to avoid deviations in measurements from images. Errors increase if wide angle lens cameras are used. Moreover, the coupling between intrinsic and extrinsic camera parameters and the lens distortion model influences the result of the calibration process notably. This paper proposes a method for calibrating wide angle lens cameras, which takes into account the existing hard coupling. The proposed method obtains stable results, which do not depend on how the image lens distortion is corrected.This work was supported in part by the Universidad Politecnica de Valencia research funds (PAID 2010-2431 and PAID 10017), the Generalitat Valenciana (GV/2011/057) and the Spanish government and the European Community under Project DPI2010-20814-C02-02 (FEDER-CICYT) and Project DPI2010-20286 (CICYT). The associate editor coordinating the review of this paper and approving it for publication was Dr. Subhas C. Mukhopadhyay.Ricolfe Viala, C.; Sánchez Salmerón, AJ.; Valera Fernández, Á. (2013). Efficient lens distortion correction for decoupling in calibration of wide angle lens cameras. IEEE Sensors Journal. 13(2):854-863. https://doi.org/10.1109/JSEN.2012.2229704S85486313

Pathfinding and positioning in a labyrinth game using a wide-angle camera

Alten AB has a technology demonstator in the form of a motorized and camera equipped large scale labyrinth game. The ball position is controlled by a ABB industrial PLC connected with Android tablets for user interface and a camera as a sensor for the ball position. This thesis demonstrates the ability to place a wide angle camera inside the cabinet, correcting the lens distortion caused by the wide angle lens and detect the ball with the use of a circular Hough transform. A path is also generated from the ball position to any position of the maze by capturing an image from the camera, generating a map for subsequent pathfinding, using an improvement of the Dijkstra’s pathfinding algorithm named Theta*. It further demonstrates the feasibility of using the computing power of the camera for both pathfinding and ball positioning

Vision based navigation system for autonomous proximity operations: an experimental and analytical study

This dissertation presents an experimental and analytical study of the Vision Based Navigation system (VisNav). VisNav is a novel intelligent optical sensor system invented by Texas A&M University recently for autonomous proximity operations. This dissertation is focused on system calibration techniques and navigation algorithms. This dissertation is composed of four parts. First, the fundamental hardware and software design configuration of the VisNav system is introduced. Second, system calibration techniques are discussed that should enable an accurate VisNav system application, as well as characterization of errors. Third, a new six degree-of-freedom navigation algorithm based on the Gaussian Least Squares Differential Correction is presented that provides a geometrical best position and attitude estimates through batch iterations. Finally, a dynamic state estimation algorithm utilizing the Extended Kalman Filter (EKF) is developed that recursively estimates position, attitude, linear velocities, and angular rates. Moreover, an approach for integration of VisNav measurements with those made by an Inertial Measuring Unit (IMU) is derived. This novel VisNav/IMU integration technique is shown to significantly improve the navigation accuracy and guarantee the robustness of the navigation system in the event of occasional dropout of VisNav data