Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …

The nascent applicability of multi-camera tracking (MCT) in numerous real-world
applications makes it a significant computer vision problem. While visual tracking of objects …

Standardized benchmarks are crucial for the majority of computer vision applications.
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …

We present a novel approach to online multi-target tracking based on recurrent neural
networks (RNNs). Tracking multiple objects in real-world scenes involves many challenges …

There is a large variety of trackers, which have been proposed in the literature during the
last two decades with some mixed success. Object tracking in realistic scenarios is a difficult …

Recent years have seen greater interest in the use of discriminative classifiers in tracking
systems, owing to their success in object detection. They are trained online with samples …

Many recent advances in multiple target tracking aim at finding a (nearly) optimal set of
trajectories within a temporal window. To handle the large space of possible trajectory …

In this paper, we focus mainly on designing a Multi-Target Object Tracking algorithm that
would produce high-quality trajectories while maintaining low computational costs. Using …

Data association is an essential component of any human tracking system. The majority of
current methods, such as bipartite matching, incorporate a limited-temporal-locality of the …

Online multi-object tracking with a single moving camera is a challenging problem as the
assumptions of 2D conventional motion models (eg, first or second order models) in the …