The typical Internet of Things application, unattended driving systems, will need the ability to
recognize relevant traffic participants and detect dangerous situations ahead of time. An …

One of the biggest challenges in multi-pedestrian tracking arises in crowds, where missing
detections can lead to wrong track-detection assignments, especially under heavy …

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 …

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

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 …

Most current online multi-object tracking (MOT) methods include two steps: object detection
and data association, where the data association step relies on both object feature …

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 this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-
resolution aerial imagery by intensive evaluation of a number of traditional and Deep …

Tracking by detection is a common approach to solving the Multiple Object Tracking
problem. In this paper we show how learning a deep similarity metric can improve three key …

Multiple pedestrian tracking faces the challenge of tracking pedestrians in the presence of
occlusion. Existing methods suffer from inaccurate motion estimation, appearance feature …