While most multi-object tracking methods based on tracking-by-detection use either spatial
or appearance cues for associating detections or apply one cue after another, our proposed …

Pedestrians are often vulnerable users of urban roads and ensuring their safety is a
pressing challenge in the filed of intelligent transportation. Multiple pedestrian tracking is …

Existing multi target multi camera tracking (MTMCT) datasets are small in terms of the
number of identities and video lengths. The creation of new real world datasets is hard as …

In this paper, we propose an efficient online multi-object tracking method based on the
Gaussian mixture probability hypothesis density (GMPHD) filter and occlusion group …

Multi-object tracking (MOT) is an important topic and critical task related to both static and
moving camera applications, such as traffic flow analysis, autonomous driving and robotic …

Most of the multi-person trackers in literature assign only high-confident detections to
already tracked targets so the full potential of available detections is not leveraged …

Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in
videos. Most methods obtain identities by associating detection boxes whose scores are …

Recently, advances in detection and re-identification techniques have significantly boosted
tracking-by-detection-based multi-pedestrian tracking (MPT) methods and made MPT a …

This paper presents an approach for tracking in a surveillance scenario. Typical aspects for
this scenario are a 24/7 operation with a static camera mounted above the height of a …

Kalman filter-based tracking-by-detection (KFTBD) trackers are effective methods for solving
multi-person tracking tasks. However, in crowd circumstances, noisy detection results …