Hungarian-Particle Filtering Based Segmentation for On-Road Visual Vehicle Detection and Tracking
Nuramin Fitri Aminuddin, Zarina Tukiran, Ariffuddin Joret, Muhammad Nuriffat Roslee, Shingo Yamaguchi, Mohd Anuaruddin Bin Ahmadon · 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech) · 2022
This work presents a method for detecting and tracking vehicles in traffic videos collected from urban highways. The method efficiently handles numerous vehicle targets with low computational complexity, making it ideal for real-time driver assisting systems. The method uses segmentation to create a quick bounding box to detect moving vehicles, while a particle filter is used to track these vehicles. The Hungarian matching algorithm is later used to solve the association of tracked vehicles in each video frame. The proposed method and an established vehicle tracking method, Camshift Meanshift tracking with Kalman filtering (CMT-KF), were compared and evaluated on the collected traffic videos. The proposed method resulted in a 52% reduction in tracking failures.