ByteTrack: Multi-Object Tracking by Associating Every Detection Box [PDF]
European Conference on Computer Vision, 2021 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 higher than a threshold.
Yifu Zhang +8 more
openalex +2 more sources
Multi-Object Tracking on SWIR Images for City Surveillance in an Edge-Computing Environment [PDF]
Sensors, 2023 Although Short-Wave Infrared (SWIR) sensors have advantages in terms of robustness in bad weather and low-light conditions, the SWIR images have not been well studied for automated object detection and tracking systems.
Jihun Park +3 more
doaj +2 more sources
HOTA: A Higher Order Metric for Evaluating Multi-object Tracking. [PDF]
Int J Comput Vis, 2021 Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association.
Luiten J +6 more
europepmc +3 more sources
Achieving Adaptive Visual Multi-Object Tracking with Unscented Kalman Filter [PDF]
Sensors, 2022 As an essential part of intelligent monitoring, behavior recognition, automatic driving, and others, the challenge of multi-object tracking is still to ensure tracking accuracy and robustness, especially in complex occlusion environments.
Guowei Zhang +5 more
doaj +2 more sources
Effective Multi-Object Tracking via Global Object Models and Object Constraint Learning [PDF]
Sensors, 2022 Effective multi-object tracking is still challenging due to the trade-off between tracking accuracy and speed. Because the recent multi-object tracking (MOT) methods leverage object appearance and motion models so as to associate detections between ...
Yong-Sang Yoo +2 more
doaj +2 more sources
DeepFusionMOT: A 3D Multi-Object Tracking Framework Based on Camera-LiDAR Fusion With Deep Association [PDF]
IEEE Robotics and Automation Letters, 2022 In the recent literature, on the one hand, many 3D multi-object tracking (MOT) works have focused on tracking accuracy and neglected computation speed, commonly by designing rather complex cost functions and feature extractors.
Xiyang Wang +4 more
openalex +3 more sources
Online Domain Adaptation for Multi-Object Tracking [PDF]
, 2015 Automatically detecting, labeling, and tracking objects in videos depends first and foremost on accurate category-level object detectors. These might, however, not always be available in practice, as acquiring high-quality large scale labeled training ...
Gaidon, Adrien, Vig, Eleonora
core +2 more sources
3D Multi-Object Tracking: A Baseline and New Evaluation Metrics [PDF]
IEEE/RJS International Conference on Intelligent RObots and Systems, 2019 3D multi-object tracking (MOT) is an essential component for many applications such as autonomous driving and assistive robotics. Recent work on 3D MOT focuses on developing accurate systems giving less attention to practical considerations such as ...
Xinshuo Weng +3 more
openalex +2 more sources
A two stage multi object tracking algorithm with transformer and attention mechanism [PDF]
Scientific ReportsIn the field of engineering safety, multi-object tracking encounters difficulties in effectively conducting object detection due to occlusion, as well as the issue of experiencing frequent switching of target identity ID switches (IDs).
Mingxing Hou +3 more
doaj +2 more sources
Efficient Single-Shot Multi-Object Tracking for Vehicles in Traffic Scenarios [PDF]
Sensors, 2021 Multi-object tracking is a significant field in computer vision since it provides essential information for video surveillance and analysis. Several different deep learning-based approaches have been developed to improve the performance of multi-object ...
Youngkeun Lee +3 more
doaj +2 more sources