Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …

Multi-person tracking is often solved with a tracking-by-detection approach that matches all
tracks and detections simultaneously based on a distance matrix. In crowded scenes …

Traffic video analytics has become one of the core components in the evolution of
transportation systems. Artificially intelligent traffic management systems apply computer …

Artificial intelligence-based surveillance system, one of the essential systems for smart cities,
plays a critical role in ensuring the safety and well-being of individuals. In this paper, we …

The implementation of multi-target multi-camera tracking systems in indoor environments
including shops and warehouses facilitates strategic product positioning and the …

This work introduces a multi-camera tracking dataset consisting of 234 hours of video data
recorded concurrently from 234 overlapping HD cameras covering a 4.2 mile stretch of 8-10 …

Joint detection and embedding (JDE) methods usually fuse the target motion information
and appearance information as the data association matrix, which could fail when the target …

Multi-camera tracking of vehicles on a city-wide level is a core component of modern traffic
monitoring systems. For this task, single-camera tracking failures are the most common …

Multi-camera tracking (MCT) plays a crucial role in various computer vision applications.
However accurate tracking of individuals across multiple cameras faces challenges …

In recent years, several methods and datasets have been proposed to push the performance
of pedestrian detection in crowded scenarios. In this study, three crowd-specific detectors …