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
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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
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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
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NCT:noise-control multi-object tracking
Complex & Intelligent Systems, 2023 Multi-Object Tracking (MOT) is an important topic in computer vision. Recent MOT methods based on the anchor-free paradigm trade complicated hierarchical structures for tracking performance.
Kai Zeng +6 more
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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
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A Review of Deep Learning-Based Visual Multi-Object Tracking Algorithms for Autonomous Driving
Applied Sciences, 2022 Multi-target tracking, a high-level vision job in computer vision, is crucial to understanding autonomous driving surroundings. Numerous top-notch multi-object tracking algorithms have evolved in recent years as a result of deep learning’s outstanding ...
Shuman Guo +7 more
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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
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Pixel-Guided Association for Multi-Object Tracking [PDF]
Sensors, 2022 Propagation and association tasks in Multi-Object Tracking (MOT) play a pivotal role in accurately linking the trajectories of moving objects. Recently, modern deep learning models have been addressing these tasks by introducing fragmented solutions for ...
Abhijeet Boragule +3 more
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M3OT: A Multi-Drone Multi-Modality dataset for Multi-Object Tracking [PDF]
Scientific DataWe provide a dataset for object detection and tracking in aerial imagery, namely “M3OT”. M3OT is a multi-modality vehicle detection and tracking dataset acquired by two Unmanned Aerial Vehicles (UAVs) in a high-altitude region, consisting both RGB and ...
Zhihao Nie +5 more
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Comparative study on dynamic visual tracking abilities in three-dimensional multi-object tracking tasks among basketball players of different skill levels [PDF]
Frontiers in PsychologyObjectiveThis study aimed to examine whether high-level basketball players exhibit superior multi-object tracking abilities compared to low-level basketball players using the three-dimensional multi-object tracking (3D-MOT) task paradigm.MethodsForty ...
Zhi Guo, Qiulin Wang
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