Tracking in urban street scenes plays a central role in autonomous systems such as self-
driving cars. Most of the current vision-based tracking methods perform tracking in the image …

The objective of extended object tracking is to simultaneously track a target object and
estimate its shape. As a consequence, it becomes necessary to incorporate both location …

In this paper, we propose a novel method for estimating an elliptic shape approximation of a
moving extended object that gives rise to multiple scattered measurements per frame. For …

With the rise of end-to-end learning through deep learning, person detectors and re-
identification (ReID) models have recently become very strong. Multi-camera multi-target …

YOLO represents the one-stage object detection also called regression-based object
detection. Object in the given input is directly classified and located instead of using the …

YOLO represents the one-stage object detection also called regression-based object
detection. Object in the given input is directly classified and located instead of using the …

The aim of this work is to formulate a new metric to be used in the automotive industry for the
evaluation process of software used to detect vehicles on video data. To achieve this goal …

Recent digital acquisition systems can acquire high-resolution videos, generating a large
amount of dynamic data and leading to higher computational cost in online target tracking …

This paper presents an approach to improving visual object tracking performance by
dynamically fusing the results of two trackers, where the scheduling of trackers is determined …

In the past decade many robots were deployed in the wild, and people detection and
tracking is an important component of such deployments. On top of that, one often needs to …