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
Information on traffic patterns is essential for identifying and addressing sources of traffic congestion and informing future road layouts to create safer and more efficient roads. To this end, we develop a Corridor Counting, or Multi- Camera Vehicle Counting, algorithm that quantifies the number of vehicles traveling along a specific stretch of road. Our work builds upon the related problem of Multi-Camera Vehicle Tracking and draws inspiration from methods used for Single-Camera Counting. We propose a six-step solution comprising Vehicle Detection, Feature Extraction, Single- Camera Vehicle Tracking, Re-Identification, Movement Matching, and Multi-Camera Vehicle Counting. Finally, we adapt an evaluation metric from Single-Camera Vehicle Counting to assess the effectiveness of our solution.
Recommended Citation
Bryson, Anthony; Zhou, Vincent; and Ha, Amy, "Corridor Counting" (2024). Computer Science and Engineering Senior Theses. 277.
https://scholarcommons.scu.edu/cseng_senior/277