Degree Type

Creative Component

Semester of Graduation

Spring 2020

Department

Statistics

First Major Professor

Heike Hofmann

Degree(s)

Master of Science (MS)

Major(s)

Statistics

Abstract

Shoe analysis is frequently used as part of forensic analysis. However, when time is factored in, the wear of the sole and its features can be difficult. Here we present a method for extracting the wear between two 3D scans of a single shoe after some amount of use, using an iterative alignment process, in order to discover matching methods after a large amount of wear. Initial processing transforms a Standard Triangle Language (stl) 3D object, into a triangle mesh before alignment. Alignment between the two meshes is accomplished using principal component analysis to initially align the mesh objects onto the same plane; followed by an iterative closest point comparison, to align via a landmark of the maximum depth of the sole. The landmarks are chosen based off of points in the specific brand that are unlikely to be worn, such as the arch or indented designs. After alignment, surface differences are measured and compared, in order to define wear. This method has been used to successfully compare wear in a variety of brands including Nike, Adidas, and Sony for wear patterns from new up to 8 months old. The methods presented here allows for more accurate wear analysis which can help the forensic community match shoe print analysis, even after wear.

Copyright Owner

Blagg, Eryn

File Format

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