Although range scanning technology has offered great improvements to digital model creation in recent years,
it has also introduced some new concerns. Specifically, recent work shows that topological errors such as tiny
handles can significantly lower the overall quality of range-scanned models for down-stream applications (such as
simplification and parameterization). In this paper we present our investigation into the source of this topological
error in the range scanning process, and our methods to alleviate the error. We concentrated our investigation of
the scanning process on: (1) signal noise or calibration error in the laser scanner (resulting in bad data points)
and (2) error during the model reconstruction phase. We found that by modifying the surface reconstruction
phase of the range scanning process, we were able to reduce the amount of topological noise in the resulting 3D
model by up to 60 percent.
For over thirty years researchers have been trying to solve the shape from shading problem of determining 3D shape from a single image with a single light source. The basic problem of determining shape from shading is made more difficult due to challenges of light orientation, camera type, ambiguity, multiple materials, and specular highlights. This paper shows how some of these challenges can be overcome through the use of other techniques such as image segmentation and stereopsis. We present a new hybrid method of shape from shading that can be used to autonomously capture 3D information from two 2D images of single objects with multiple peaks and multiple materials with specular components.
We present a visualization and computation tool for modeling the caloric cost of pedestrian travel across three dimensional terrains. This tool is being used in ongoing archaeological research that analyzes how costs of locomotion affect the spatial distribution of trails and artifacts across archaeological landscapes. Throughout human history, traveling by foot has been the most common form of transportation, and therefore analyses of pedestrian travel costs are important for understanding prehistoric patterns of resource acquisition, migration, trade, and political interaction. Traditionally, archaeologists have measured geographic proximity based on "as the crow flies" distance. We propose new methods for terrain visualization and analysis based on measuring paths of least caloric expense, calculated using well established metabolic equations. Our approach provides a human centered metric of geographic closeness, and overcomes significant limitations of available Geographic Information System (GIS) software. We demonstrate such path computations and visualizations applied to archaeological research questions. Our system includes tools to visualize: energetic cost surfaces, comparisons of the elevation profiles of shortest paths versus least cost paths, and the display of paths of least caloric effort on Digital Elevation Models (DEMs). These analysis tools can be applied to calculate and visualize 1) likely locations of prehistoric trails and 2) expected ratios of raw material types to be recovered at archaeological sites.