Thesis (Ph. D.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 135-143). Also available on the Internet.

Understanding, monitoring and managing savanna ecosystems require characterizing both functional and structural properties of vegetation. Due to functional diversity and structural heterogeneity in savannas, characterizing these properties using remote sensing is methodologically challenging. Focusing on the semi-arid savanna in the central Kalahari, the objective of this dissertation was to combine in situ data with multi-scale satellite imagery and two image analysis approaches (i.e. Multiple Endmember Spectral Mixture Analysis (MESMA) and Object Based Image Analysis (OBIA)) to : (i) determine the superior method for estimating fractional photosynthetic vegetation (fPV), non-photosynthetic vegetation (fNPV) and bare soil (fBS) when high spatial resolution multispectral imagery is used, (ii) examine the suitability of OBIA for mapping vegetation morphology types using a Landsat TM imagery, (iii) examine the impact of changing spatial resolution on magnitude and accuracy of fractional cover and (iv) examine how the fractional cover magnitude and accuracy are spatially associated with vegetation morphology. Using the GeoEye-1 imagery, MESMA provided more accurate fractional cover estimates than OBIA. The increasing segmentation scale in OBIA resulted in a consistent increase in error. While areas under woody cover produced lower errors even at coarse segmentation scales, those with herbaceous cover provided low errors only at the fine segmentation scale. Vegetation morphology type mapping results suggest that classes with dominant woody life forms attained higher accuracy at fine segmentation scales, while those with dominant herbaceous vegetation reached higher classification accuracy at coarse segmentation scales. Contrarily, for bare areas accuracy was relatively unaffected by changing segmentation scale. Multi-scale fractional cover mapping results indicate that increasing pixel size caused consistent increases in variance of and error in fractional cover estimates. Even at a coarse spatial resolution, fPV was estimated with higher accuracy compared to fNPV and fBS. At a larger pixel size, in areas with dominant woody vegetation, fPV was overestimated at the cost of mainly underestimating fBS; in contrast, in areas with dominant herbaceous vegetation, fNPV was overestimated with a corresponding underestimation of both fPV and fBS. These results underscore that structural and functional heterogeneity in savannas impact retrieval of fractional cover, suggesting that comprehensive remote sensing of savannas needs to take both structure and cover into account. / text

With its mixing of real and virtual, Augmented Reality (AR) is a technology that has attracted lots of attention from the science community and is seen as a perfect way to visualize context-related information. Computer generated graphics is presented to the user overlaid and registered with the real world and hence augmenting it. Promising intelligence amplification and higher productivity, AR has been intensively researched over several decades but has yet to reach a broad audience. This thesis presents efforts in bringing Augmented Reality to mobile phones and thus to the general public. Implementing technologies on limited devices, such as mobile phones, poses a number of challenges that differ from traditional research directions. These include: limited computational resources with little or no possibility to upgrade or add hardware, limited input and output capabilities for interactive 3D graphics. The research presented in this thesis addresses these challenges and makes contributions in the following areas: Mobile Phone Computer Vision-Based Tracking The first contribution of thesis has been to migrate computer vision algorithms for tracking the mobile phone camera in a real world reference frame - a key enabling technology for AR. To tackle performance issues, low-level optimized code, using fixed-point algorithms, has been developed. Mobile Phone 3D Interaction Techniques Another contribution of this thesis has been to research interaction techniques for manipulating virtual content. This is in part realized by exploiting camera tracking for position-controlled interaction where motion of the device is used as input. Gesture input, made possible by a separate front camera, is another approach that is investigated. The obtained results are not unique to AR and could also be applicable to general mobile 3D graphics. Novel Single User AR Applications With short range communication technologies, mobile phones can exchange data not only with other phones but also with an intelligent environment. Data can be obtained for tracking or visualization; displays can be used to render graphics with the tracked mobile phone acting as an interaction device. Work is presented where a mobile phone harvests a sensor-network to use AR to visualize live data in context. Novel Collaboration AR Applications One of the most promising areas for mobile phone based AR is enhancing face-to-face computer supported cooperative work. This is because the AR display permits non-verbal cues to be used to a larger extent. In this thesis, face-to-face collaboration has been researched to examine whether AR increases awareness of collaboration partners even on small devices such as mobile phones. User feedback indicates that this is the case, confirming the hypothesis that mobile phones are increasingly able to deliver an AR experience to a large audience. / On the day of the defence date the status on articles III and VIII was: Accepted.

D. Tech. Electrical Engineering. / In the past few years, mesh representation of images has attracted a lot of research interest due to its wide area of applications in image processing. Mesh representation showed encouraging results for image segmentation, reconstruction and compression. The present work revisits the Laplacian mesh smoothing, a technique for fairing surfaces, almost exclusively applied to 3D meshes. The report is also based on the idea that while sampling points in an image are distributed uniformly, the information in an image is not following a uniform distribution. Instead of filtering the gray levels of the image, the proposed method, called grid smoothing, filter the coordinates of the sampling points of the image.

The visual appearance of an image is a complex function of factors such as scene geometry, material reflectances and textures, illumination, and the properties of the camera used to capture the image. Understanding how these factors interact to produce an image is a fundamental problem in computer vision and graphics. This dissertation examines two aspects of this problem: models of visual appearance that allow us to recover scene properties from images and videos, and tools that allow users to manipulate visual appearance in images and videos in intuitive ways. In particular, we look at these problems in three different applications. First, we propose techniques for compositing images that differ significantly in their appearance. Our framework transfers appearance between images by manipulating the different levels of a multi-scale decomposition of the image. This allows users to create realistic composites with minimal interaction in a number of different scenarios. We also discuss techniques for compositing and replacing facial performances in videos. Second, we look at the problem of creating high-quality still images from low-quality video clips. Traditional multi-image enhancement techniques accomplish this by inverting the camera’s imaging process. Our system incorporates feature weights into these image models to create results that have better resolution, noise, and blur characteristics, and summarize the activity in the video. Finally, we analyze variations in scene appearance caused by changes in lighting. We develop a model for outdoor scene appearance that allows us to recover radiometric and geometric infor- mation about the scene from images. We apply this model to a variety of visual tasks, including color-constancy, background subtraction, shadow detection, scene reconstruction, and camera geo-location. We also show that the appearance of a Lambertian scene can be modeled as a combi- nation of distinct three-dimensional illumination subspaces — a result that leads to novel bounds on scene appearance, and a robust uncalibrated photometric stereo method. / Engineering and Applied Sciences

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

The present work expose a technique of estimation of optimal direction for placing dental implant. A volumetric computed tomography (CT) scan is used as a help of the following searches. The work offers criteria of the optimal implant placement direction and methods of evaluation on direction’s significance. The technique utilizes structure tensor to find a normal to the jawbone surface. Direction of that normal is then used as initial direction for search of optimal direction. The technique described in the present work aimed to support doctor’s decisions during dental implantation treatment.

Geodesic Tractography Segmentation is the two component approach presented in this thesis for the analysis of imagery in oriented domains, with emphasis on the application to diffusion-weighted magnetic resonance imagery (DW-MRI). The computeraided analysis of DW-MRI data presents a new set of problems and opportunities for the application of mathematical and computer vision techniques. The goal is to develop a set of tools that enable clinicians to better understand DW-MRI data and ultimately shed new light on biological processes. This thesis presents a few techniques and tools which may be used to automatically find and segment major neural fiber bundles from DW-MRI data. For each technique, we provide a brief overview of the advantages and limitations of our approach relative to other available approaches. / Acknowledgements page removed per author's request, 01/06/2014.

<p>Tree-like structures are fundamental in nature. A wide variety of two-dimensional imaging techniques allow us to image trees. However, an image of a tree typically includes spurious branch crossings and the original relationships of ancestry among edges may be lost. We present a methodology for estimating the most likely topology of a rooted, directed, three-dimensional tree given a single two-dimensional image of it. We regularize this inverse problem via a prior parametric tree-growth model that realistically captures the morphology of a wide variety of trees. We show that the problem of estimating the optimal tree has linear complexity if ancestry is known, but is NP-hard if it is lost. For the latter case, we present both a greedy approximation algorithm and a heuristic search algorithm that effectively explore the space of possible trees. Experimental results on retinal vessel, plant root, and synthetic tree datasets show that our methodology is both accurate and efficient.</p> / Dissertation