Shoeprint Matching

Shoeprint matching aims to automatically identify matches between crime scene prints and shoes, a crucial task in forensic science. Current research focuses on improving the accuracy and generalizability of machine learning models, often employing techniques like iterative closest point (ICP) alignment and random forests, by leveraging large datasets of online shoe images and developing methods to estimate 3D tread depth maps from 2D photos. These advancements address limitations of existing methods in handling noisy, partial, or worn prints, ultimately enhancing the reliability and efficiency of forensic investigations.