Date of Award
6-18-2024
Document Type
Thesis
Publisher
Santa Clara : Santa Clara University, 2024
Department
Computer Science and Engineering
First Advisor
David Anastasiu
Abstract
The possibility of an efficient and accurate solution for multi-camera people tracking (MCPT) is enabled by the improvement of computing power and the advancement of machine learning technologies. The problem of multi-camera people tracking serves as a cornerstone of real-world applications such as video surveillance or warehouse automation. The current solutions for MCPT suffer from problems such as appearance inconsistency, object occlusion, etc. Our work targets tackling the challenges faced by modern MCPT algorithms to bring a more robust, efficient, and accurate solution.
Recommended Citation
Haque, Eerina; Huang, Eric; and Li, Sihang, "Two-Step Hierarchical Multi-Camera People Tracking" (2024). Computer Science and Engineering Senior Theses. 303.
https://scholarcommons.scu.edu/cseng_senior/303