Multiple object tracking: A literature review
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 …
and commercial potential. Although different approaches have been proposed to tackle this …
[HTML][HTML] Multi-camera multi-object tracking: a review of current trends and future advances
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 …
applications makes it a significant computer vision problem. While visual tracking of objects …
Deep affinity network for multiple object tracking
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 …
problems in video analysis and computer vision. Most MOT methods employ two steps …
MOT16: A benchmark for multi-object tracking
Standardized benchmarks are crucial for the majority of computer vision applications.
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …
Unifying short and long-term tracking with graph hierarchies
O Cetintas, G Brasó… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Tracking objects over long videos effectively means solving a spectrum of problems, from
short-term association for un-occluded objects to long-term association for objects that are …
short-term association for un-occluded objects to long-term association for objects that are …
Multiple hypothesis tracking revisited
This paper revisits the classical multiple hypotheses tracking (MHT) algorithm in a tracking-
by-detection framework. The success of MHT largely depends on the ability to maintain a …
by-detection framework. The success of MHT largely depends on the ability to maintain a …
Motchallenge 2015: Towards a benchmark for multi-target tracking
In the recent past, the computer vision community has developed centralized benchmarks
for the performance evaluation of a variety of tasks, including generic object and pedestrian …
for the performance evaluation of a variety of tasks, including generic object and pedestrian …
Online multi-target tracking using recurrent neural networks
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 …
networks (RNNs). Tracking multiple objects in real-world scenes involves many challenges …
Learning to track: Online multi-object tracking by decision making
Abstract Online Multi-Object Tracking (MOT) has wide applications in time-critical video
analysis scenarios, such as robot navigation and autonomous driving. In tracking-by …
analysis scenarios, such as robot navigation and autonomous driving. In tracking-by …
Learning a proposal classifier for multiple object tracking
P Dai, R Weng, W Choi, C Zhang… - Proceedings of the …, 2021 - openaccess.thecvf.com
The recent trend in multiple object tracking (MOT) is heading towards leveraging deep
learning to boost the tracking performance. However, it is not trivial to solve the data …
learning to boost the tracking performance. However, it is not trivial to solve the data …