In this thesis, an image-based uncalibrated visual servo is proposed for image tracking tasks in highly disturbed environment, such as a remotely operated vehicle performing observing or investigation objects under the influence of undersea current. For the conditions that the target model and the camera parameters are unknown, the control framework applies the scale invariant feature transform (SIFT) to extract image features. Furthermore, a robust adaptive control law is implemented to overcome the effect caused by camera calibration parameters. Then by using three different types of camera¡¦s motion: pan, tilt, and zoom to maintain the target always at the central position on the image plane.

A picture of a scene is a 2-dimensional representation of a 3-dimensional world. In the process of projecting the scene onto the 2-dimensional image plane, some of the information about the 3-dimensional scene is inevitably lost. Given a series of images of a scene, typically taken by a video camera, it is sometimes possible to recover some of this lost 3-dimensional information. Within the computer vision literature this process is described as that of recovering structure from motion. If some of the information about the internal geometry of the camera is unknown, then the problem is described as that of recovering structure from motion in the uncalibrated case. It is this uncalibrated version of the problem that is the concern of this thesis. Optical flow represents the movement of points across the image plane over time. Previous work in the area of structure from motion has given rise to a so-called differential epipolar equation which describes the relationship between optical flow and the motion and internal parameters of the camera. This equation allows the calibration of a camera undergoing unknown motion and having an unknown, and possibly varying, focal length. Obtaining accurate estimates of the camera motion and internal parameters in the presence of noisy optical flow data is critical to the structure recovery process. We present and compare a variety of methods for estimating the coefficients of the differential epipolar equation. The goal of this process is to derive a tractable total least squares estimator of structure from motion robust to the presence of inaccuracies in the data. Methods are also presented for rectifying optical flow to a particular motion estimates, eliminating outliers from the data, and calculating the relative motion of a camera over an image sequence. This thesis thus explores the application of numerical and statistical techniques for the estimation of structure from motion in the uncalibrated case. / Thesis (Ph.D.)--Mathematical and Computer Sciences (Department of Computer Science), 2000.

No description available.

Generation of photo-realistic 3D human face models is a hot topic in the area joining computer graphics and computer vision. Many different techniques are used for this purpose, but most of them are not feasible for home users. These techniques may use advanced hardware such as laser scanners, calibrated stereo cameras, or very sophisticated software that can be as expensive as advanced hardware. Face model generation by morphing an initial 3D model with uncalibrated camera photographs is studied in this thesis. Manually marked feature points on photographs are used to deform initial 3D face model. Initial photographs also are processed to form a single texture image covering deformed 3D face model.

No / Design of iterative learning control (ILC) often requires some prior knowledge about a system's control matrix. In some applications, such as uncalibrated visual servoing, this kind of knowledge may be unavailable so that a stable learning control cannot always be achieved. In this paper, a universal ILC is proposed for a class of multi-input multi-output (MIMO) uncertain nonlinear systems with no prior knowledge about the system control gain matrix. It consists of a gain matrix selector from the unmixing set and a learned compensator in a form of the positive definite discrete matrix kernel, corresponding to rough gain matrix probing and refined uncertainty compensating, respectively. Asymptotic convergence for a trajectory tracking within a finite time interval is achieved through repetitive tracking. Simulations and experiments of uncalibrated visual servoing are carried out in order to verify the validity of the proposed control method.

Much research effort has been devoted to producing algorithms that contribute directly or indirectly to the extraction of 3D information from a wide variety of types of scenes and conditions of image capture. The research work presented in this thesis is aimed at three distinct applications in this area: interactively extracting 3D points from a pair of uncalibrated images in a flexible way; finding corresponding points automatically in high resolution images, particularly those of archaeological scenes captured from a freely moving light aircraft; and improving a correlation approach to dense disparity mapping leading to 3D surface reconstructions. The fundamental concepts required to describe the principles of stereo vision, the camera models, and the epipolar geometry described by the fundamental matrix are introduced, followed by a detailed literature review of existing methods. An interactive system for viewing a scene via a monochrome or colour anaglyph is presented which allows the user to choose the level of compromise between amount of colour and ghosting perceived by controlling colour saturation, and to choose the depth plane of interest. An improved method of extracting 3D coordinates from disparity values when there is significant error is presented. Interactive methods, while very flexible, require significant effort from the user finding and fusing corresponding points and the thesis continues by presenting several variants of existing scale invariant feature transform methods to automatically find correspondences in uncalibrated high resolution aerial images with improved speed and memory requirements. In addition, a contribution to estimating lens distortion correction by a Levenberg Marquard based method is presented; generating data strings for straight lines which are essential input for estimating lens distortion correction. The remainder of the thesis presents correlation based methods for generating dense disparity maps based on single and multiple image rectifications using sets of automatically found correspondences and demonstrates improvements obtained using the latter method. Some example views of point clouds for 3D surfaces produced from pairs of uncalibrated images using the methods presented in the thesis are included.

Uncalibrated visual servoing (VS) can improve robot performance without needing camera and robot parameters. Multiple cameras improve uncalibrated VS precision, but no works exist simultaneously using more than two cameras. The first data for uncalibrated VS simultaneously using more than two cameras are presented. VS performance is also compared for two different camera models: a high-cost camera and a low-cost camera, the difference being image noise magnitude and focal length. A Kalman filter based control law for uncalibrated VS is introduced and shown to be stable under the assumptions that robot joint level servo control can reach commanded joint offsets and that the servoing path goes through at least one full column rank robot configuration. Adaptive filtering by a covariance matching technique is applied to achieve automatic camera weighting, prioritizing the best available data. A decentralized sensor fusion architecture is utilized to assure continuous servoing with camera occlusion. The decentralized adaptive Kalman filter (DAKF) control law is compared to a classical method, Gauss-Newton, via simulation and experimentation. Numerical results show that DAKF can improve average tracking error for moving targets and convergence time to static targets. DAKF reduces system sensitivity to noise and poor camera placement, yielding smaller outliers than Gauss-Newton. The DAKF system improves visual servoing performance, simplicity, and reliability.

Much research effort has been devoted to producing algorithms that contribute directly or indirectly to the extraction of 3D information from a wide variety of types of scenes and conditions of image capture. The research work presented in this thesis is aimed at three distinct applications in this area: interactively extracting 3D points from a pair of uncalibrated images in a flexible way; finding corresponding points automatically in high resolution images, particularly those of archaeological scenes captured from a freely moving light aircraft; and improving a correlation approach to dense disparity mapping leading to 3D surface reconstructions. The fundamental concepts required to describe the principles of stereo vision, the camera models, and the epipolar geometry described by the fundamental matrix are introduced, followed by a detailed literature review of existing methods. An interactive system for viewing a scene via a monochrome or colour anaglyph is presented which allows the user to choose the level of compromise between amount of colour and ghosting perceived by controlling colour saturation, and to choose the depth plane of interest. An improved method of extracting 3D coordinates from disparity values when there is significant error is presented. Interactive methods, while very flexible, require significant effort from the user finding and fusing corresponding points and the thesis continues by presenting several variants of existing scale invariant feature transform methods to automatically find correspondences in uncalibrated high resolution aerial images with improved speed and memory requirements. In addition, a contribution to estimating lens distortion correction by a Levenberg Marquard based method is presented; generating data strings for straight lines which are essential input for estimating lens distortion correction. The remainder of the thesis presents correlation based methods for generating dense disparity maps based on single and multiple image rectifications using sets of automatically found correspondences and demonstrates improvements obtained using the latter method. Some example views of point clouds for 3D surfaces produced from pairs of uncalibrated images using the methods presented in the thesis are included. / Al-Baath University / The appendices files and images are not available online.

This thesis considers the problem of tracking an object in world coordinates using measurements obtained from multiple uncalibrated cameras. A general approach to track the location of a target involves different phases including calibrating the camera, detecting the object's feature points over frames, tracking the object over frames and analyzing object's motion and behavior. The approach contains two stages. First, the problem of camera calibration using a calibration object is studied. This approach retrieves the camera parameters from the known locations of ground data in 3D and their corresponding image coordinates. The next important part of this work is to develop an automated system to estimate the trajectory of the object in 3D from image sequences. This is achieved by combining, adapting and integrating several state-of-the-art algorithms. Synthetic data based on a nearly constant velocity object motion model is used to evaluate the performance of camera calibration and state estimation algorithms.

A crescente capacidade do poder computacional e a proliferação de dispositivos ao nosso redor vem permitindo o desenvolvimento de novas e sofisticadas interfaces para interação humano-computador que reagem à presença e ao estado de seus usuários. Como o olhar tem a capacidade de transmitir muitas informações sobre o usuário, rastreadores de olhar, dispositivos que estimam a direção para onde uma pessoa olha, tem papel importante no desenvolvimento de tais interfaces. Entre suas aplicações temos o auxílio a pessoas com dificuldades motoras, que podem utilizar um rastreador de olhar como substituto ao mouse, aplicações de diagnóstico, que estudam evidências do comportamento humano, ou ainda o desenvolvimento de interfaces que utilizem a informação sobre o olhar como um canal a mais de comunicação com o usuário para perceber suas intenções. Muitas técnicas para atingir tal objetivo foram desenvolvidas mas as tradicionais ainda oferecem certas dificuldades de uso para seus usuários como a intolerância a movimentos de cabeça e a necessidade de calibração por sessão de uso. Neste trabalho fizemos um levantamento de uma série de técnicas de rastreamento de olhar, indo das mais tradicionais até algumas mais recentes que visam melhorar a facilidade de uso destes sistemas. Uma das técnicas mais promissoras utiliza múltiplas fontes de luz fixadas nos cantos do monitor do computador. Através da análise da posição dos reflexos gerados por essas fontes de luz sobre a córnea, juntamente com a informação da posição da pupila, presentes em imagens capturadas do olho, é possível estimar o ponto observado no monitor. Devido às suas vantagens ela foi escolhida para estudo mais detalhado e implementação. Extensos testes utilizando simulações foram realizados para avaliar seu desempenho. Foi também desenvolvida uma extensão dessa técnica, utilizando um modelo mais preciso do olho, visando melhorar sua precisão. Ao final apresentamos nossa implementação, baseada nessa extensão da técnica original, que é tolerante a movimentação da face e mostramos os resultados obtidos em testes realizados com um grupo de usuários. / Recent advances in computing power and the proliferation of computing devices around us allowed the development of new computer interfaces which can react to the presence and state of its users. Since gaze can transmit a lot of information about the user, gaze trackers, devices that can estimate the direction which a person is looking at, have an important role in the development of such interfaces. Among gaze tracking applications, we have aid for people with limited motor skills, human behavior studies, and the development of interfaces that can take gaze information as an additional communication channel with the user. Lots of techniques have been developed to reach this goal, but they have some problems that make them hard to be widely used. These problems are the need of calibration for each use session and the need to keep the user\'s head still. In this work we studied some of the existing gaze tracking techniques, from the more traditional ones to more recent ones. One of the most interesting techniques makes use of multiple light sources fixed at the monitor\'s corners. By analyzing the positions of corneal reflections and the pupil present in captured images of the eye, it is possible to estimate the gaze point on the monitor screen. Due to its advantages this technique was chosen for a deeper study and implementation. Lots of experiments using simulated data have been carried out to validate the technique. Using a more accurate model of the eye, an extension for this technique was also developed to increase its precision. Finally, we present our implementation, that allows for large head movement, as well as test results obtained from real users.