Scalable and Real-time Multi-Camera Vehicle Detection, Re-Identification, and Tracking

TL;DR

This paper presents a scalable, real-time multi-camera vehicle tracking system capable of handling low-resolution CCTV footage for large-scale transportation analysis, outperforming many existing methods in practical scenarios.

Contribution

The authors introduce a practical, real-time multi-camera vehicle tracking system optimized for low-resolution videos, addressing computational challenges and deployment at city scale.

Findings

Ranked among top five in NVIDIA AI City challenge

Handles low-resolution CCTV footage effectively

Operates in real-time at city scale

Abstract

Multi-camera vehicle tracking is one of the most complicated tasks in Computer Vision as it involves distinct tasks including Vehicle Detection, Tracking, and Re-identification. Despite the challenges, multi-camera vehicle tracking has immense potential in transportation applications including speed, volume, origin-destination (O-D), and routing data generation. Several recent works have addressed the multi-camera tracking problem. However, most of the effort has gone towards improving accuracy on high-quality benchmark datasets while disregarding lower camera resolutions, compression artifacts and the overwhelming amount of computational power and time needed to carry out this task on its edge and thus making it prohibitive for large-scale and real-time deployment. Therefore, in this work we shed light on practical issues that should be addressed for the design of a multi-camera tracking system to provide actionable and timely insights. Moreover, we propose a real-time city-scale multi-camera vehicle tracking system that compares favorably to computationally intensive alternatives and handles real-world, low-resolution CCTV instead of idealized and curated video streams. To show its effectiveness, in addition to integration into the Regional Integrated Transportation Information System (RITIS), we participated in the 2021 NVIDIA AI City multi-camera tracking challenge and our method is ranked among the top five performers on the public leaderboard.