Showing papers by "David H. Laidlaw published in 2002"

Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning

Abstract: A heretofore unsolved problem of great archaeological importance is the automatic assembly of pots made on a wheel from the hundreds (or thousands) of sherds found at an excavation site. An approach is presented to the automatic estimation of mathematical models of such pots from 3D measurements of sherds. A Bayesian approach is formulated beginning with a description of the complete set of geometric parameters that determine the distribution of the sherd measurement data. Matching of fragments and aligning them geometrically into configurations is based on matching break-curves (curves on a pot surface separating fragments), estimated axis and profile curve pairs for individual fragments and configurations of fragments, and a number of features of groups of break-curves. Pot assembly is a bottom-up maximum likelihood performance-based search. Experiments are illustrated on pots which were broken for the purpose, and on sherds from an archaeological dig located in Petra, Jordan. The performance measure can also be an aposteriori probability, and many other types of information can be included, e.g., pot wall thickness, surface color, patterns on the surface, etc. This can also be viewed as the problem of learning a geometric object from an unorganized set of free-form fragments of the object and of clutter, or as a problem of perceptual grouping.

Discovering Petra: archaeological analysis in VR

Abstract: New tools give archaeologists access to formerly inaccessible parts of the archaeological record. The result is a demonstrably improved model for inquiry to pose, and answer, important research questions. We chronicle a collaborative effort (from 1997 to the present) with Petra Great Temple archaeologists to augment traditional analysis approaches. We introduce new archaeological analysis tools that combine novel visualization and interaction techniques within a Cave Automatic Virtual Environment (CAVE).

Fitting manifold surfaces to three-dimensional point clouds.

Abstract: We present a technique for fitting a smooth, locally parameterized surface model (called the manifold surface model) to unevenly scattered data describing an anatomical structure. These data are acquired from medical imaging modalities such as CT scans or MRI. The manifold surface is useful for problems which require analyzable or parametric surfaces fitted to data acquired from surfaces of arbitrary topology (e.g., entire bones). This surface modeling work is part of a larger project to model and analyze skeletal joints, in particular the complex of small bones within the wrist and hand. To demonstrate the suitability of this model we fit to several different bones in the hand, and to the same bone from multiple people.

Fitting Manifold Surfaces To 3D Point Clouds

Abstract: We present a technique for fitting a smooth, locally parameterized surface model (called the manifold surface model) to unevenly scattered data describing an anatomical structure. This data is acquired from medical imaging modalities such as CT scans or MRI. The manifold surface is useful for problems which require analyzable or parametric surfaces fitted to data acquired from surfaces of arbitrary topology (e.g., entire bones). This surface modeling work is part of a larger project to model and analyze skeletal joints, in particular the complex of small bones within the wrist and hand. To demonstrate the suitability of this model we fit to several different bones in the hand, and to the same bone from multiple people. CR Categories: I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling, Surface Additional

Toward a framework for assembling broken pottery vessels

Abstract: This paper addresses how to automatically reconstruct pottery vessels from a collection of sherds using a variety of features and their comparisons. To solve the problem, we designed a computational framework that is founded on the primitive operations of “match” proposal and evaluation. A match defines the geometric relationship between a pair of sherds. This framework affords a natural decomposition of the computation required by an automatic assembly process and provides a concrete basis to evaluate the utility of different features and feature comparisons for assembly. Pairwise matches are proposed and subsequently evaluated by a series of independent feature similarity modules. Assembly strategies are abstracted from the feature-specific sherd details and operate solely in terms of the probabilistic output of pair-wise proposals and evaluations. Our framework, which is modular and extensible, paves the way for a system to automatically reconstruct pottery vessels. We demonstrate a greedy assembly strategy that predicts likely pairs and triples of sherds using a handful of proposal and evaluation modules. Previous attempts to automate the task of reconstructing pottery vessels have relied on a single feature, and sometimes user intervention, to direct the search (Ucoluk & Toroslu 1999), (Papaioannou, Karabassi, & Theoharis 2001), (da Gama Leito & Stolfi 1998). While (Cooper et al. 2001) accounts for more than one feature using complex parametric models, we propose a conceptually simpler and modular system for integration akin to (Pankanti, Jain, & Tuceryan 1994) and (Keim et al. 1999; Keim, Shazeer, & Littman 1999). Our framework and assembly strategy are similar to (Jepson & Mann 1999) where they search for a plausible scene interpretation.

Visualization of Contact Areas and Ligament Paths in Joints

Abstract: We demonstrate a method for visualizing contact areas and ligament paths in articular joints. Contact areas define the cortical surface where bones articulate with each other. Visualization of contact areas and ligament paths has the potential to non-invasively highlight subtle but important differences between injured and uninjured joints. Animations of these visualizations are particularly helpful for understanding changes in relationships among bones. We applied our technique to the distal radioulnar joint of a volunteer diagnosed with malunited distal radial fracture in one forearm. Our approach highlights modifications in injured forearm kinematics previously undetected.