Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 24 for “"distance functions"”.
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Differentiable volume rendering using signed distance functions
… represent geometry within the scene as a signed distance function. We also present methods for performing gradient descent upon distance fields while preserving Lipschitz continuity. Unlike most differentiable mesh-based renderers, our renderer can optimize between geometry of different …
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An investigation of assignment rules for fitting new subjects into clusters established by hierarchical pattern analysis
… approach to the problem, namely, the use of distance functions as a means of identifying subjects as members of types which had been established by hierarchical pattern analysis. A sample of subjects was drawn randomly from a population; these subjects were assigned to the types that appeared …
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First-order geometric evolutions and semilinear evolution equations : a common mutational approach
… of derivatives as first-order approximations, distance functions (maybe in a generalized sense) are required and essentially the only tool to use for a general approach beyond vector spaces. Here two concepts are presented, both of which are based on generalizing the mutational equations of …
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Cosmological constraints using 2- and 3-point correlations with meerkat, the ska and other surveys
… be for constraining cosmological parameters, BAO distance functions, growth function, and what they mean for dynamical dark energy and modified gravity. We account for telescope beam effects, instrumental noise, foreground avoidance, the Alcock-Paczynski effect, and theoretical modeling errors in …
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Active geometric model : multi-compartment model-based segmentation & registration
… shape descriptor, namely the Multi-Compartment Distance Functions or mcdf. Our proposed framework for segmentation is two-fold: first, several training samples distributed across various classes are registered onto a common frame of reference; then, we use a variational method similar to Active …
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Robust object pose estimation with point clouds from vision and touch
… articulated object tracker based on signed-distance functions. This tracker runs at 12 Hz using an online depth reconstruction algorithm for the GelSight tactile sensor and a modified second-order update for the tracking algorithm. The tracker provides robust pose estimates of small objects …
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A Feasibility Problem Approach For Reachable Set Approximation
… based on optimally controlled problems with distance functions as objectives. It was initially described 2009 by Baier and Gerdts. The advanced approach works without minimizing objective functions and is based on pure feasibility problems. Many of these feasibility problems are solved in …
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Distance based heterogeneous volume modelling.
… changes digitally can be problematic. Attribute functions represent physical properties distribution in the volumetric object. Modelling complex attributes within a volume is a complex task. There are several approaches to modelling attributes, but distance functions have gained popularity for …
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On analysing deformable (moving) objects
… these features which we formulate as continuous functions can be modelled by linear PCA.<br/><br/>This thesis also proposes a new fast and robust shape registration algorithm to match shapes from different sources in the proposed framework. This algorithm is based on linear orthogonal …
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In search of better proximity
… by disjoint balls (of arbitrary radii), and the distance of a query point to a ball is the distance to the ball as a set. (iii) We consider more general distance functions and proximity search queries on them. This translates to the abstract problem of computing the lower envelope of a set of …
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Signed distance registration for depth image sequence
… data. Thus, from our analysis of ideal signed distance functions, we propose a new method for finding the closest point to the surface given a signed distance function and its gradient. Utilizing Implicit Moving Least Squares (IMLS) and our analysis, we propose a new algorithm that computes the …
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Determinants of Southern Nevada in-migration: Similarities and differences between labor force and elderly migrants
… migrating to Nevada. Also, as might be expected, distance functions as a major barrier, discouraging both labor force and elderly migrants from relocating to Nevada. In addition, for labor force migrants, relatively high personal income growth and high unemployment rates in the states of origin …
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Learning image segmentation and hierarchies by learning ultrametric distances
… hierarchy learning based on ultrametric distance functions. It is well-known that the connectivity of neural networks in the brain can have a dramatic influence on their computational function . However, our understanding of the complete connectivity of neural circuits has been quite …
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The role of proximity in human-agent trust
… research proposes that proximity—beyond physical distance—functions as a multidimensional construct that governs how humans perceive, interpret, and calibrate trust toward agents. Across three studies, this dissertation systematically investigates these dimensions. Study 1 explored visual …
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Where am I? - Indoor localization based on range measurements
… circumvent these problems, we use the concept of distance functions, which model the resemblance between the sensor data and the map, and appropriately adapt the above method to the needs of realistic scenarios. In particular, we introduce a distance function, namely the polar coordinate metric, …
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Searching business process models by example
… contributes a conceptual notion of behavioral distance that quantifies commonalities and differences of a pair of process models, and enables process model search. Based on behavioral distances, a set of measures is proposed that evaluate the quality of a particular search result to guide the …
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Quasi-Monte Carlo and Picard Iteration Algorithms for the Nonlinear Hydrodynamics, Dynamics and Controls of Wave Energy Converters
… mesh-free geometric representation using signed distance functions circumvents the numerically sensitive mesh-mesh surface intersection at each time step, and a continuously differentiable boundary blur accelerates the QMC convergence. These algorithms have been implemented in a parallel-time …
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Low dimensional visualization and modelling of data using distance-based models
… in machine learning, namely, the choice of a distance function to describe the similarity of two data points. Often, implicit choices are made, e.g., a spatial scale is chosen to compare images, or features are weighted in a certain way. Unfortunately, different distance functions can yield …
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Fully Automated Segmentation of High Grade Serous Ovarian Cancer on Computed Tomography Images using Deep Learning
… automated segmentations including mathematical distance functions and clinical assessments. Thereafter, we will consider the segmentation of the full disease burden, including very small and rare lesions. For this, different multi-class segmentation approaches are compared, and hyper-parameter …
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Parametric curve and Partial Differential Equation-based parametric surface reconstruction from point clouds
… implicit representations encom- pass level sets, distance functions, and Constructive Solid Ge- ometry (CSG), among others. Parametric models are especially popular in 3D modelling, design, and manufacturing because they are mathematically defined, making them easy to edit, transmit, and …
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