This paper provides a literature review of some of the most important concepts, techniques,
and methodologies used within autonomous car systems. Specifically, we focus on two …

Deep learning (DL) has made breakthroughs in many computer vision tasks and also in
visual tracking. From the beginning of the research on the automatic acquisition of high …

Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …

Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …

Multiple Object Tracking (MOT) plays an important role in solving many fundamental
problems in video analysis and computer vision. Most MOT methods employ two steps …

Data association-based multiple object tracking (MOT) involves multiple separated modules
processed or optimized differently, which results in complex method design and requires …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

Current popular online multi-object tracking (MOT) solutions apply single object trackers
(SOTs) to capture object motions, while often requiring an extra affinity network to associate …

A graph structure is a powerful mathematical abstraction, which can not only represent
information about individuals but also capture the interactions between individuals for …

The deep learning technique has proven to be effective in the classification and localization
of objects on the image or ground plane over time. The strength of the technique's features …