Theses Defense

Zhaopeng Cui - PhD Depth Examination

PhD Depth Examination: Camera Pose Estimation in Structure-From-Motion - Zhaopeng Cui

Abstract:

Structure-from-motion (SfM) is a fundamental problem in computer vision. It refers to the process of estimating 3d scene structures and camera poses simultaneously from multiple 2d images. Conventional SfM systems often consist of three steps:

1) estimation of point correspondences and relative poses between images

2) estimation of camera motions and 3d points, and

PhD Thesis Defense: Topology-Varying Shape Matching and Modelling - Ibraheem Alhashim

The automatic creation of man-made 3D objects is an active area in computer graphics. Mixing and blending of components or sub components from existing example shapes can help users quickly produce interesting and creative designs. A key factor for automating this task is using computer algorithms that can map between objects of different shape and structure. However, due to the coarse correspondence computed by current matching algorithms, automatic shape blending is mainly limited to the substitution of compatible part sets.

PhD Thesis Defence: Shape Compaction via Stacking and Folding- Honghua Li

Space-saving, or collapsible, objects are ubiquitous in our living and working space. They can adjust configurations to either perform their intended functionality or save space, for example, while storing and shipping. This additional space-saving characteristic of collapsible objects comparing to their non-collapsible counterparts makes them more preferable, especially in environments where space is costly.

MSc Thesis Defence:A Non-Local Approach to Tree Peak Detection in LIDAR Data- Ssushant Joshi

The majority of existing methods for delineating trees from LIDAR point cloud use a region growing approach. Seed points representing the highest point of the trees (tree-peaks) are detected in the point cloud. The remaining points are iteratively assigned to one of the seed points, thus growing the region representing trees. The tree-peak detection methodologies are based on local geometry analysis, identifying locally highest points within some appropriately sized neighborhood as tree-peaks.

MSc Thesis Defence: Explicit Memory Management for Mesh Traversal -Yuan(Karen) Liu

Abstract
Mesh traversal is a common and essential geometry processing problem in computer graphics. The traversal typically processes each face in a mesh in a systematic and consistent order for different applications such as mesh compression, rendering and mesh simplification. While cache-efficient mesh traversal methods where data and computations are reordered for good cache reuse have been well-studied, their performances are limited by implicit(automatic) memory management. In this work we explore optimizations on Explicitly Managed Memory (EMM) systems.
 

M.Sc. Thesis Defense: Detail-Replicating Shape Stretching - Ibraheem Alhashim

Abstract:
Mesh deformation methods are useful for creating shape variations. Existing deformation techniques work on preserving surface details under bending and twisting operations. Stretching different parts of a shape is also a useful operation for generating shape variations. Under stretching, texture-like geometric details should not be preserved but rather replicated. We propose a simple method that help create model variation by applying non-uniform stretching on 3D models.

M.Sc. Thesis Defence: A Comparative Study of Spectral Embedding Methods - Xiaoming Li

Abstract:
Spectral methods, which employ eigenvalues, eigenvectors, or eigenspace projections derived from linear operators, have been proposed in the computer science literature in recent decades. In the area of geometry processing and analysis, various spectral methods have been developed and used to solve a diversity of problems, such as shape classification, graph partitioning, mesh parameterization, mesh segmentation, shape correspondence, and symmetry detection.

M.Sc. Thesis Defence: VISMON: Facilitating Analysis of Trade-Offs, Uncertainty and Sensitivity in Fisheries Management Decision Making - Maryam Booshehrian

Abstract:
Vismon is designed to support sophisticated data analysis of simulation results by managers who are highly knowledgeable about the fisheries domain but not experts in statistical data analysis. The features of Vismon include sensitivity analysis, comprehensive and global trade-offs analysis, and a staged approach to visualization of the uncertainty of the underlying simulation model.

Ph.D. Thesis Defense: Data Processing on the Body-Centered Cubic Lattice - Usman Alim

Abstract:
The body-centered cubic (BCC) lattice is the optimal three-dimensional
sampling lattice. In order to approximate a scalar-valued function
from samples that reside on a BCC lattice, spline-like compact kernels
have been recently proposed. The lattice translates of an admissible
BCC kernel form a shift-invariant approximation space that yields
higher quality approximations as compared to similar spline-like
spaces associated with the ubiquitous Cartesian cubic (CC) lattice.

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