2019/07/27 by Xavier Francis, Hamid Sharifzadeh, Francis, Xavier +7
Computer Science · Medicine · #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #Diabetic Foot Ulcer Assessment and Management #FOS: Computer and information sciences #Human Pose and Action Recognition
paper · pdf · doi:10.48550/arxiv.1907.12005
openalex publication_date 2019/07/27 · openalex created_date 2022/07/19 · openalex updated_date 2026/07/28
Footwear outsoles acquire characteristics unique to the individual wearing\nthem over time. Forensic scientists largely rely on their skills and knowledge,\ngained through years of experience, to analyse such characteristics on a\nshoeprint. In this work, we present a convolutional neural network model that\ncan predict the wear pattern on a unique dataset of shoeprints that captures\nthe life and wear of a pair of shoes. We present an additional architecture\nable to reconstruct the outsole back to its original state on a given week, and\nprovide empirical evaluations of the performance of both models.\n