69 research outputs found

    Visually Augmented Navigation in an Unstructured Environment Using a Delayed State History

    Full text link
    This paper describes a framework for sensor fusion of navigation data with camera-based 5 DOF relative pose measurements for 6 DOF vehicle motion in an unstructured 3D underwater environment. The fundamental goal of this work is to concurrently sstimate online current vehicle position and its past trajectory. This goal is framed within the context of improving mobile robot navigation to support sub-sea science and exploration. Vehicle trajectory is represented by a history of poses in an augmented state Kalman filter. Camera spatial constraints from overlapping imagery provide partial observation of these posa and are used to enforce consislency and provide a mechanism for loop-closure. The multi-sensor camera+navigation framework is shown to have compelling advantages over a camera-only based approach by 1) improving the robustness of pairwise image registration, 2) setting the free gauge scale, and 3) allowing for a unconnected camera graph topology. Results are shown for a real world data set collected by an autonomous underwater vehicle in an unstructured undersea environment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86055/1/reustice-32.pd

    Contextual cropping and scaling of TV productions

    Get PDF
    This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-011-0804-3. Copyright @ Springer Science+Business Media, LLC 2011.In this paper, an application is presented which automatically adapts SDTV (Standard Definition Television) sports productions to smaller displays through intelligent cropping and scaling. It crops regions of interest of sports productions based on a smart combination of production metadata and systematic video analysis methods. This approach allows a context-based composition of cropped images. It provides a differentiation between the original SD version of the production and the processed one adapted to the requirements for mobile TV. The system has been comprehensively evaluated by comparing the outcome of the proposed method with manually and statically cropped versions, as well as with non-cropped versions. Envisaged is the integration of the tool in post-production and live workflows

    THREE-DIMENSIONAL VISION FOR STRUCTURE AND MOTION ESTIMATION

    Get PDF
    1997/1998Questa tesi, intitolata Visione Tridimensionale per la stima di Struttura e Moto, tratta di tecniche di Visione Artificiale per la stima delle proprietà geometriche del mondo tridimensionale a partire da immagini numeriche. Queste proprietà sono essenziali per il riconoscimento e la classificazione di oggetti, la navigazione di veicoli mobili autonomi, il reverse engineering e la sintesi di ambienti virtuali. In particolare, saranno descritti i moduli coinvolti nel calcolo della struttura della scena a partire dalle immagini, e verranno presentati contributi originali nei seguenti campi. Rettificazione di immagini steroscopiche. Viene presentato un nuovo algoritmo per la rettificazione, il quale trasforma una coppia di immagini stereoscopiche in maniera che punti corrispondenti giacciano su linee orizzontali con lo stesso indice. Prove sperimentali dimostrano il corretto comportamento del metodo, come pure la trascurabile perdita di accuratezza nella ricostruzione tridimensionale quando questa sia ottenuta direttamente dalle immagini rettificate. Calcolo delle corrispondenze in immagini stereoscopiche. Viene analizzato il problema della stereovisione e viene presentato un un nuovo ed efficiente algoritmo per l'identificazione di coppie di punti corrispondenti, capace di calcolare in modo robusto la disparità stereoscopica anche in presenza di occlusioni. L'algoritmo, chiamato SMW, usa uno schema multi-finestra adattativo assieme al controllo di coerenza destra-sinistra per calcolare la disparità e l'incertezza associata. Gli esperimenti condotti con immagini sintetiche e reali mostrano che SMW sortisce un miglioramento in accuratezza ed efficienza rispetto a metodi simili Inseguimento di punti salienti. L'inseguitore di punti salienti di Shi-Tomasi- Kanade viene migliorato introducendo uno schema automatico per lo scarto di punti spuri basato sulla diagnostica robusta dei campioni periferici ( outliers ). Gli esperimenti con immagini sintetiche e reali confermano il miglioramento rispetto al metodo originale, sia qualitativamente che quantitativamente. Ricostruzione non calibrata. Viene presentata una rassegna ragionata dei metodi per la ricostruzione di un modello tridimensionale della scena, a partire da una telecamera che si muove liberamente e di cui non sono noti i parametri interni. Il contributo consiste nel fornire una visione critica e unificata delle più recenti tecniche. Una tale rassegna non esiste ancora in letterarura. Moto tridimensionale. Viene proposto un algoritmo robusto per registrate e calcolare le corrispondenze in due insiemi di punti tridimensionali nei quali vi sia un numero significativo di elementi mancanti. Il metodo, chiamato RICP, sfrutta la stima robusta con la Minima Mediana dei Quadrati per eliminare l'effetto dei campioni periferici. Il confronto sperimentale con una tecnica simile, ICP, mostra la superiore robustezza e affidabilità di RICP.This thesis addresses computer vision techniques estimating geometrie properties of the 3-D world /rom digital images. Such properties are essential for object recognition and classification, mobile robots navigation, reverse engineering and synthesis of virtual environments. In particular, this thesis describes the modules involved in the computation of the structure of a scene given some images, and offers original contributions in the following fields. Stereo pairs rectification. A novel rectification algorithm is presented, which transform a stereo pair in such a way that corresponding points in the two images lie on horizontal lines with the same index. Experimental tests prove the correct behavior of the method, as well as the negligible decrease oLthe accuracy of 3-D reconstruction if performed from the rectified images directly. Stereo matching. The problem of computational stereopsis is analyzed, and a new, efficient stereo matching algorithm addressing robust disparity estimation in the presence of occlusions is presented. The algorithm, called SMW, is an adaptive, multi-window scheme using left-right consistency to compute disparity and its associated uncertainty. Experiments with both synthetic and real stereo pairs show how SMW improves on closely related techniques for both accuracy and efficiency. Features tracking. The Shi-Tomasi-Kanade feature tracker is improved by introducing an automatic scheme for rejecting spurious features, based on robust outlier diagnostics. Experiments with real and synthetic images confirm the improvement over the original tracker, both qualitatively and quantitatively. 111 Uncalibrated vision. A review on techniques for computing a three-dimensional model of a scene from a single moving camera, with unconstrained motion and unknown parameters is presented. The contribution is to give a critical, unified view of some of the most promising techniques. Such review does not yet exist in the literature. 3-D motion. A robust algorithm for registering and finding correspondences in two sets of 3-D points with significant percentages of missing data is proposed. The method, called RICP, exploits LMedS robust estimation to withstand the effect of outliers. Experimental comparison with a closely related technique, ICP, shows RICP's superior robustness and reliability.XI Ciclo1968Versione digitalizzata della tesi di dottorato cartacea

    Large-area visually augmented navigation for autonomous underwater vehicles

    Get PDF
    Submitted to the Joint Program in Applied Ocean Science & Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2005This thesis describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of autonomous underwater vehicles (AUVs) while exploiting the inertial sensor information that is routinely available on such platforms. We adopt a systems-level approach exploiting the complementary aspects of inertial sensing and visual perception from a calibrated pose-instrumented platform. This systems-level strategy yields a robust solution to underwater imaging that overcomes many of the unique challenges of a marine environment (e.g., unstructured terrain, low-overlap imagery, moving light source). Our large-area SLAM algorithm recursively incorporates relative-pose constraints using a view-based representation that exploits exact sparsity in the Gaussian canonical form. This sparsity allows for efficient O(n) update complexity in the number of images composing the view-based map by utilizing recent multilevel relaxation techniques. We show that our algorithmic formulation is inherently sparse unlike other feature-based canonical SLAM algorithms, which impose sparseness via pruning approximations. In particular, we investigate the sparsification methodology employed by sparse extended information filters (SEIFs) and offer new insight as to why, and how, its approximation can lead to inconsistencies in the estimated state errors. Lastly, we present a novel algorithm for efficiently extracting consistent marginal covariances useful for data association from the information matrix. In summary, this thesis advances the current state-of-the-art in underwater visual navigation by demonstrating end-to-end automatic processing of the largest visually navigated dataset to date using data collected from a survey of the RMS Titanic (path length over 3 km and 3100 m2 of mapped area). This accomplishment embodies the summed contributions of this thesis to several current SLAM research issues including scalability, 6 degree of freedom motion, unstructured environments, and visual perception.This work was funded in part by the CenSSIS ERC of the National Science Foundation under grant EEC-9986821, in part by the Woods Hole Oceanographic Institution through a grant from the Penzance Foundation, and in part by a NDSEG Fellowship awarded through the Department of Defense

    Theorems and algorithms for multiple view geometry with applications to electron tomography

    Get PDF
    The thesis considers both theory and algorithms for geometric computer vision. The framework of the work is built around the application of autonomous transmission electron microscope image registration. The theoretical part of the thesis first develops a consistent robust estimator that is evaluated in estimating two view geometry with both affine and projective camera models. The uncertainty of the fundamental matrix is similarly estimated robustly, and the previous observation whether the covariance matrix of the fundamental matrix contains disparity information of the scene is explained and its utilization in matching is discussed. For point tracking purposes, a reliable wavelet-based matching technique and two EM algorithms for the maximum likelihood affine reconstruction under missing data are proposed. The thesis additionally discusses identification of degeneracy as well as affine bundle adjustment. The application part of the thesis considers transmission electron microscope image registration, first with fiducial gold markers and thereafter without markers. Both methods utilize the techniques proposed in the theoretical part of the thesis and, in addition, a graph matching method is proposed for matching gold markers. Conversely, alignment without markers is disposed by tracking interest points of the intensity surface of the images. At the present level of development, the former method is more accurate but the latter is appropriate for situations where fiducial markers cannot be used. Perhaps the most significant result of the thesis is the proposed robust estimator because of consistence proof and its many application areas, which are not limited to the computer vision field. The other algorithms could be found useful in multiple view applications in computer vision that have to deal with uncertainty, matching, tracking, and reconstruction. From the viewpoint of image registration, the thesis further achieved its aims since two accurate image alignment methods are suggested for obtaining the most exact reconstructions in electron tomography.reviewe
    • …
    corecore