Tangent-ball techniques for shape processing

Shape processing defines a set of theoretical and algorithmic tools for creating, measuring and modifying digital representations of shapes.  Such tools are of paramount importance to many disciplines of computer graphics, including modeling, animation, visualization, and image processing.  Many applications of shape processing can be found in the entertainment and medical industries. In an attempt to improve upon many previous shape processing techniques, the present thesis explores the theoretical and algorithmic aspects of a difference measure, which involves fitting a ball (disk in 2D and sphere in 3D) so that it has at least one tangential contact with each shape and the ball interior is disjoint from both shapes. We propose a set of ball-based operators and discuss their properties, implementations, and applications.  We divide the group of ball-based operations into unary and binary as follows: Unary operators include: * Identifying details (sharp, salient features, constrictions) * Smoothing shapes by removing such details, replacing them by fillets and roundings * Segmentation (recognition, abstract modelization via centerline and radius variation) of tubular structures Binary operators include: * Measuring the local discrepancy between two shapes * Computing the average of two shapes * Computing point-to-point correspondence between two shapes * Computing circular trajectories between corresponding points that meet both shapes at right angles * Using these trajectories to support smooth morphing (inbetweening) * Using a curve morph to construct surfaces that interpolate between contours on consecutive slices The technical contributions of this thesis focus on the implementation of these tangent-ball operators and their usefulness in applications of shape processing. We show specific applications in the areas of animation and computer-aided medical diagnosis.  These algorithms are simple to implement, mathematically elegant, and fast to execute.Ph.D.Committee Chair: Jarek Rossignac; Committee Member: Greg Slabaugh; Committee Member: Greg Turk; Committee Member: Karen Liu; Committee Member: Maryann Simmon

The State-of-the-Art of Set Visualization

Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net

Cubic Planar Graphs That Cannot Be Drawn On Few Lines

For every integer l, we construct a cubic 3-vertex-connected planar bipartite graph G with O(l^3) vertices such that there is no planar straight-line drawing of G whose vertices all lie on l lines. This strengthens previous results on graphs that cannot be drawn on few lines, which constructed significantly larger maximal planar graphs. We also find apex-trees and cubic bipartite series-parallel graphs that cannot be drawn on a bounded number of lines

Curve-Based Shape Matching Methods and Applications

One of the main cues we use in our everyday life when interacting with the environment is shape. For example, we use shape information to recognise a chair, grasp a cup, perceive traffic signs and solve jigsaw puzzles. We also use shape when dealing with more sophisticated tasks, such as the medical diagnosis of radiographs or the restoration of archaeological artifacts. While the perception of shape and its use is a natural ability of human beings, endowing machines with such skills is not straightforward. However, the exploitation of shape cues is important for the development of competent computer methods that will automatically perform tasks such as those just mentioned. With this aim, the present work proposes computer methods which use shape to tackle two important tasks, namely packing and object recognition. The packing problem arises in a variety of applications in industry, where the placement of a set of two-dimensional shapes on a surface such that no shapes overlap and the uncovered surface area is minimised is important. Given that this problem is NP-complete, we propose a heuristic method which searches for a solution of good quality, though not necessarily the optimal one, within a reasonable computation time. The proposed method adopts a pictorial representation and employs a greedy algorithm which uses a shape matching module in order to dynamically select the order and the pose of the parts to be placed based on the “gaps” appearing in the layout during the execution. This thesis further investigates shape matching in the context of object recognition and first considers the case where the target object and the input scene are represented by their silhouettes. Two distinct methods are proposed; the first method follows a local string matching approach, while the second one adopts a global optimisation approach using dynamic programming. Their use of silhouettes, however, rules out the consideration of any internal contours that might appear in the input scene, and in order to address this limitation, we later propose a graph-based scheme that performs shape matching incorporating information from both internal and external contours. Finally, we lift the assumption made that input data are available in the form of closed curves, and present a method which can robustly perform object recognition using curve fragments (edges) as input evidence. Experiments conducted with synthetic and real images, involving rigid and deformable objects, show the robustness of the proposed methods with respect to geometrical transformations, heavy clutter and substantial occlusion

Autonomous parafoil guidance in high winds

Thesis (M.Sc.Eng.)Guided airdrop systems lacking propulsion may be adversely affected by high winds. Strong winds encountered during Draper Laboratory flight testing prevented lightweight parafoil systems from landing accurately. This thesis introduces and compares multiple guidance strategies designed to address high wind scenarios in cases of differing wind knowledge fidelity. The algorithms presented significantly improve performance in high tailwind and shifting wind scenarios without compromising miss accuracy in standard wind conditions. This adds additional capability to parafoil guidance by substantially increasing the conditions under which accurate landings are possible