General Defocusing Particle Tracking: fundamentals and uncertainty assessment
Experiments in Fluids, 2020 General Defocusing Particle Tracking (GDPT) is a single-camera, three-dimensional particle tracking method that determines the particle depth positions from the defocusing patterns of the corresponding particle images.
Barnkob, Rune, Rossi, Massimiliano
core +2 more sources
Bias in particle tracking acceleration measurement [PDF]
Experiments in Fluids, 2018 We investigate sources of error in acceleration statistics from Lagrangian Particle Tracking (LPT) data and demonstrate techniques to eliminate or minimise bias errors introduced during processing.
Bodenschatz, Eberhard +3 more
core +2 more sources
Long axial range 3D single-particle tracking using birefringent substrates [PDF]
Nature Communications3D single-particle tracking is a critical imaging technique for visualizing molecular motion in complex environments, including biological cells.
Shuho Nozue +3 more
doaj +2 more sources
Micro-Scale Particle Tracking: From Conventional to Data-Driven Methods [PDF]
MicromachinesMicro-scale positioning techniques have become essential in numerous engineering systems. In the field of fluid mechanics, particle tracking velocimetry (PTV) stands out as a key method for tracking individual particles and reconstructing flow fields ...
Haoyu Wang +2 more
doaj +2 more sources
Performance of a geometric deep learning pipeline for HL-LHC particle tracking [PDF]
The European Physical Journal C, 2021 The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. Exa.TrkX’s tracking pipeline groups detector measurements to form track candidates and filters them.
X. Ju +23 more
semanticscholar +1 more source
3D Turning Target Tracking Method Based on Particle Filter [PDF]
Hangkong bingqi, 2022 In order to improve the tracking accuracy of turning targets, a 3D turning target tracking method based on particle filter is proposed. Aiming at the HGB maneuvering target in 3D space, this article first proposes a 3D turning motion model and ...
Feng Yaqiang, Song Long, Zhang Gongping
doaj +1 more source
Charged Particle Tracking via Edge-Classifying Interaction Networks [PDF]
Computing and Software for Big Science, 2021 Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high-energy particle physics.
G. Dezoort +7 more
semanticscholar +1 more source
Graph Neural Networks for Charged Particle Tracking on FPGAs [PDF]
Frontiers in Big Data, 2021 The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase of ...
Abdelrahman Elabd +12 more
semanticscholar +1 more source
SerialTrack: ScalE and rotation invariant augmented Lagrangian particle tracking
SoftwareX, 2022 We present a new particle tracking algorithm for accurately resolving large deformation and rotational motion fields, which takes advantage of both local and global particle tracking algorithms.
Jin Yang +9 more
doaj +1 more source
Particle Filter Based on Harris Hawks Optimization Algorithm for Underwater Visual Tracking
Journal of Marine Science and Engineering, 2023 Due to the complexity of the underwater environment, tracking underwater targets via traditional particle filters is a challenging task. To resolve the problem that the tracking accuracy of a traditional particle filter is low due to the sample ...
Junyi Yang, Yutong Yao, Donghe Yang
doaj +1 more source