Multi-pedestrian trackers perform well when targets are clearly visible making the
association task quite easy. However, when heavy occlusions are present, a mechanism to …

This work addresses the task of multi-person tracking in crowded street scenes, where long-
term occlusions pose a major challenge. One popular way to address this challenge is to re …

The association task of assigning detections to tracks in multi-person tracking has recently
been improved by integration of a second matching stage for low-confident detections that …

Most multiple people tracking systems compute trajectories based on the tracking-by-
detection paradigm. Consequently, the performance depends to a large extent on the quality …

In this paper we propose an approach for articulated tracking of multiple people in
unconstrained videos. Our starting point is a model that resembles existing architectures for …

Multiple pedestrian tracking (MPT) has gained significant attention due to its huge potential
in a commercial application. It aims to predict multiple pedestrian trajectories and maintain …

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 …

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 …

Tracking-by-detection is one of the typical paradigms for multi-person tracking, due to the
availability of automatic pedestrian detectors. However, existing multi-person trackers are …

In online multi-target tracking, modeling of appearance and geometric similarities between
pedestrians visual scenes is of great importance. The higher dimension of inherent …