Método para el registro automático de imágenes basado en transformaciones proyectivas planas dependientes de las distancias y orientado a imágenes sin características comunes

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Arquitectura de Computadores y Automática, leída el 18-12-2015Multisensory data fusion oriented to image-based application improves the accuracy, quality and availability of the data, and consequently, the performance of robotic systems, by means of combining the information of a scene acquired from multiple and different sources into a unified representation of the 3D world scene, which is more enlightening and enriching for the subsequent image processing, improving either the reliability by using the redundant information, or the capability by taking advantage of complementary information. Image registration is one of the most relevant steps in image fusion techniques. This procedure aims the geometrical alignment of two or more images. Normally, this process relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. For instance, in the combination of ToF and RGB cameras, the robust feature-matching is not reliable. Typically, the fusion of these two sensors has been addressed from the computation of the cameras calibration parameters for coordinate transformation between them. As a result, a low resolution colour depth map is provided. For improving the resolution of these maps and reducing the loss of colour information, extrapolation techniques are adopted. A crucial issue for computing high quality and accurate dense maps is the presence of noise in the depth measurement from the ToF camera, which is normally reduced by means of sensor calibration and filtering techniques. However, the filtering methods, implemented for the data extrapolation and denoising, usually over-smooth the data, reducing consequently the accuracy of the registration procedure...La fusión multisensorial orientada a aplicaciones de procesamiento de imágenes, conocida como fusión de imágenes, es una técnica que permite mejorar la exactitud, la calidad y la disponibilidad de datos de un entorno tridimensional, que a su vez permite mejorar el rendimiento y la operatividad de sistemas robóticos. Dicha fusión, se consigue mediante la combinación de la información adquirida por múltiples y diversas fuentes de captura de datos, la cual se agrupa del tal forma que se obtiene una mejor representación del entorno 3D, que es mucho más ilustrativa y enriquecedora para la implementación de métodos de procesamiento de imágenes. Con ello se consigue una mejora en la fiabilidad y capacidad del sistema, empleando la información redundante que ha sido adquirida por múltiples sensores. El registro de imágenes es uno de los procedimientos más importantes que componen la fusión de imágenes. El objetivo principal del registro de imágenes es la consecución de la alineación geométrica entre dos o más imágenes. Normalmente, este proceso depende de técnicas de búsqueda de patrones comunes entre imágenes, lo cual puede ser un inconveniente cuando se combinan sensores que no proporcionan datos con características similares. Un ejemplo de ello, es la fusión de cámaras de color de alta resolución (RGB) con cámaras de Tiempo de Vuelo de baja resolución (Time-of-Flight (ToF)), con las cuales no es posible conseguir una detección robusta de patrones comunes entre las imágenes capturadas por ambos sensores. Por lo general, la fusión entre estas cámaras se realiza mediante el cálculo de los parámetros de calibración de las mismas, que permiten realizar la trasformación homogénea entre ellas. Y como resultado de este xii Abstract procedimiento, se obtienen mapas de profundad y de color de baja resolución. Con el objetivo de mejorar la resolución de estos mapas y de evitar la pérdida de información de color, se utilizan diversas técnicas de extrapolación de datos. Un factor crucial a tomar en cuenta para la obtención de mapas de alta calidad y alta exactitud, es la presencia de ruido en las medidas de profundidad obtenidas por las cámaras ToF. Este problema, normalmente se reduce mediante la calibración de estos sensores y con técnicas de filtrado de datos. Sin embargo, las técnicas de filtrado utilizadas, tanto para la interpolación de datos, como para la reducción del ruido, suelen producir el sobre-alisamiento de los datos originales, lo cual reduce la exactitud del registro de imágenes...Sección Deptal. de Arquitectura de Computadores y Automática (Físicas)Fac. de Ciencias FísicasTRUEunpu

A coordinated UAV deployment based on stereovision reconnaissance for low risk water assessment

Biologists and management authorities such as the World Health Organisation require monitoring of water pollution for adequate management of aquatic ecosystems. Current water sampling techniques based on human samplers are time consuming, slow and restrictive. This thesis takes advantage of the recent affordability and higher flexibility of Unmanned Aerial Vehicles (UAVs) to provide innovative solutions to the problem. The proposed solution involves having one UAV, “the leader”, equipped with sensors that are capable of accurately estimating the wave height in an aquatic environment, if the region identified by the leader is characterised as having a low wave height, the area is deemed suitable for landing. A second UAV, “the follower UAV”, equipped with a payload such as an Autonomous Underwater Vehicle (AUV) can proceed to the location identified by the leader, land and deploy the AUV into the water body for the purposes of water sampling. The thesis acknowledges there are two main challenges to overcome in order to develop the proposed framework. Firstly, developing a sensor to accurately measure the height of a wave and secondly, achieving cooperative control of two UAVs. Two identical cameras utilising a stereovision approach were developed for capturing three-dimensional information of the wave distribution in a non-invasive manner. As with most innovations, laboratory based testing was necessary before a full-scale implementation can be attempted. Preliminary results indicate that provided a suitable stereo matching algorithm is applied, one can generate a dense 3D reconstruction of the surface to allow estimation of the wave height parameters. Stereo measurements show good agreement with the results obtained from a wave probe in both the time and frequency domain. The mean absolute error for the average wave height and the significant wave height is less than 1cm from the acquired time series data set. A formation-flying algorithm was developed to allow cooperative control between two UAVs. Results show that the follower was able to successfully track the leader’s trajectory and in addition maintain the given separation distance from the leader to within 1m tolerance through the course of the experiments despite windy conditions, low sampling rate and poor accuracy of the GPS sensors. In the closing section of the thesis, near real-time dense 3D reconstruction and wave height estimation from the reconstructed 3D points is demonstrated for an aquatic body using the leader UAV. Results show that for a pair of images taken at a resolution of 320 by 240 pixels up to 21,000 3D points can be generated to provide a dense 3D reconstruction of the water surface within the field of view of the cameras

What can two images tell us about a third one

This paper discusses the problem of predicting image features in an image from image features in two other images and the epipolar geometry between the three images. We adopt the most general camera model of perspective projection and show that a point can be predicted in the third image as a bilinear function of its images in the first two cameras, that the tangents to three corresponding curves are related by a trilinear function, and that the curvature of a curve in the third image is a linear function of the curvatures at the corresponding points in the other two images. Our analysis relies heavily on the use of the fundamental matrix which has been recently introduced and on the properties of a special plane which we call the trifocal plane. We thus answer completely the following question : given two views of an object, what would a third view look like ? the question and its answer bear upon several areas of computer vision, stereo, motion analysis, and model-based object recognition. Our answer is quite general since it assumes the general perspective projection model for image formation and requires only the knowledge of the epipolar geometry for the triple of views. We show that in the special case of orthographic projection our results for points reduce to those of Ullman and Basri. We demonstrate on synthetic as well as on real data the applicability of our theory

Segment-based stereo matching algorithm with rectification for single-lens bi-prism stereovision system

Ph.DDOCTOR OF PHILOSOPH

Large Area 3D Reconstructions from Underwater Surveys

Robotic underwater vehicles can perform vast optical surveys of the ocean floor. Scientists value these surveys since optical images offer high levels of information and are easily interpreted by humans. Unfortunately the coverage of a single image is limited hy absorption and backscatter while what is needed is an overall view of the survey area. Recent work on underwater mosaics assume planar scenes and are applicable only to Situations without much relief. We present a complete and validated system for processing optical images acquired from an underwater mbotic vehicle to form a 3D reconstruction of the wean floor. Our approach is designed for the most general conditions of wide-baseline imagery (low overlap and presence of significant 3D structure) and scales to hundreds of images. We only assume a calibrated camera system and a vehicle with uncertain and possibly drifting pose information (e.g. a compass, depth sensor and a Doppler velocity Our approach is based on a combination of techniques from computer vision, photogrammetry and mhotics. We use a local to global approach to structure from motion, aided by the navigation sensors on the vehicle to generate 3D suhmaps. These suhmaps are then placed in a common reference frame that is refined by matching overlapping submaps. The final stage of processing is a bundle adjustment that provides the 3D structure, camera poses and uncertainty estimates in a consistent reference frame. We present results with ground-truth for structure as well as results from an oceanographic survey over a coral reef covering an area of appmximately one hundred square meters.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86037/1/opizarro-33.pd

Accurate 3D shape and displacement measurement using a scanning electron microscope

With the current development of nano-technology, there exists an increasing demand for three-dimensional shape and deformation measurements at this reduced-length scale in the field of materials research. Images acquired by \ud Scanning Electron Microscope (SEM) systems coupled with analysis by Digital Image Correlation (DIC) is an interesting combination for development of a high magnification measurement system. However, a SEM is designed for visualization, not for metrological studies, and the application of DIC to the micro- or nano-scale with such a system faces the challenges of calibrating the imaging system and correcting the spatially-varying and \ud time-varying distortions in order to obtain accurate measurements. Moreover, the SEM provides only a single sensor and recovering 3D information is not possible with the classical stereo-vision approach. But the specimen being mounted on the mobile SEM stage, images can be acquired from multiple viewpoints and 3D reconstruction is possible using the principle of videogrammetry for recovering the unknown rigid-body motions undergone by \ud the specimen.\ud The dissertation emphasizes the new calibration methodology that has been developed because it is a major contribution for the accuracy of 3D shape and deformation measurements at reduced-length scale. It proves that, unlike previous works, image drift and distortion must be taken into account if accurate measurements are to be made with such a system. Necessary background and required theoretical knowledge for the 3D shape measurement using videogrammetry and for in-plane and out-of-plane deformation measurement are presented in details as well. In order to validate our work and demonstrate in particular the obtained measurement accuracy, experimental results resulting from different applications are presented throughout the different chapters. At last, a software gathering different computer vision applications has been developed.\ud Avec le développement actuel des nano-technologies, la demande en matière d'étude du comportement des matériaux à des échelles micro ou nanoscopique ne cesse d'augmenter. Pour la mesure de forme ou de déformations tridimensionnelles à ces échelles de grandeur,l'acquisition d'images à partir d'un Microscope électronique à Balayage (MEB) couplée à l'analyse par corrélation d'images numériques s'est avérée une technique intéressante. \ud Cependant, un MEB est un outil conçu essentiellement pour de la visualisation et son utilisation pour des mesures tridimensionnelles précises pose un certain nombre de difficultés comme par exemple le calibrage du système et la \ud correction des fortes distorsions (spatiales et temporelles) présentes dans les images. De plus, le MEB ne possède qu'un seul capteur et les informations tridimensionnelles souhaitées ne peuvent pas être obtenues par une approche classique de type stéréovision. Cependant, l'échantillon à analyser étant monté sur un support orientable, des images peuvent être acquises sous différents points de vue, ce qui permet une reconstruction tridimensionnelle en utilisant le principe de vidéogrammétrie pour retrouver à partir des seules images les mouvements inconnus du porte-échantillon.\ud La thèse met l'accent sur la nouvelle technique de calibrage et de correction des distorsions développée car c'est une contribution majeure pour la précision de la mesure de forme et de déformations 3D aux échelles de \ud grandeur étudiées. Elle prouve que, contrairement aux travaux précédents, la prise en compte de la dérive temporelle et des distorsions spatiales d'images \ud est indispensable pour obtenir une précision de mesure suffisante. Les principes permettant la mesure de forme par vidéogrammétrie et le calcul de déformations 2D et 3D sont aussi présentés en détails. Enfin, et dans le but de valider nos travaux et démontrer en particulier la précision de mesure obtenue, des résultats expérimentaux issus de différentes applications sont présentés.\ud \ud \u

Stereo Correspondence and Depth Recovery of Single-lens Bi-prism Based Stereovision System

Ph.DDOCTOR OF PHILOSOPH

Methods for Augmented Reality E-commerce

A new type of e-commerce system and related techniques are presented in this dissertation that customers of this type of e-commerce could visually bring product into their physical environment for interaction. The development and user study of this e-commerce system are provided. A new modeling method, which recovers 3D model directly from 2D photos without knowing camera information, is also presented to reduce the modeling cost of this new type of e-commerce. Also an immersive AR environment with GPU based occlusion is also presented to improve the rendering and usability of AR applications. Experiment results and data show the validity of these new technologies

Spectrally encoded fiber-based structured lighting probe for intraoperative 3D imaging

Three dimensional quantification of organ shape and structure during minimally invasive surgery (MIS) could enhance precision by allowing the registration of multi-modal or pre-operative image data (US/MRI/CT) with the live optical image. Structured illumination is one technique to obtain 3D information through the projection of a known pattern onto the tissue, although currently these systems tend to be used only for macroscopic imaging or open procedures rather than in endoscopy. To account for occlusions, where a projected feature may be hidden from view and/or confused with a neighboring point, a flexible multispectral structured illumination probe has been developed that labels each projected point with a specific wavelength using a supercontinuum laser. When imaged by a standard endoscope camera they can then be segmented using their RGB values, and their 3D coordinates calculated after camera calibration. The probe itself is sufficiently small (1.7 mm diameter) to allow it to be used in the biopsy channel of commonly used medical endoscopes. Surgical robots could therefore also employ this technology to solve navigation and visualization problems in MIS, and help to develop advanced surgical procedures such as natural orifice translumenal endoscopic surgery