@inproceedings{e3a7b5a145c845e39e32fedf0dbe3119,
title = "Tomographic three-dimensional position measurement of particles using a light field camera",
abstract = "The tracing particle plays a key role in measuring velocity of flow field. The accuracy of tracing particle's spatial localization determines the accuracy of flow field velocity measurement. The traditional multi-camera technology for photographing tracing particles is costly and time consuming. A light field camera is used to collect particle images, and improves tomographic inversion algorithm to obtain the three-dimensional spatial position of particles faster and more accurately. Based on imaging principle of the light field camera system, a forward tracking model of light emitted by particles is established to realize the imaging simulation of particles. On the basis of this model, a tomographic inversion model is constructed to reversely trace the ray and realize the mapping between non-zero pixels and spatial voxels. A descending dimension method is proposed to calculate the weighting matrix. Multiplicative algebraic reconstruction technology is improved by combined with the similar triangle principle. The Gaussian Blob model is used to determine center position of the voxel with largest intensity value to obtain the three-dimensional position of particles. Experiments indicate that the improved MART algorithm which is used to perform three-dimensional inversion of particles can significantly increase calculation efficiency under the same accuracy level. It is more suitable for applications requiring high calculation speed. The x-axis coordinate error is ±0.06mm. The y-axis coordinate error is ±0.07mm. The z-axis coordinate error is ±0.58mm.",
keywords = "Light field camera, Particle localization, Ray tracing, Tomography",
author = "Zhao Jun and Gu Gaofei and Kong Ming and Guo Tiantai and Wang Daodang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 14th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2019 ; Conference date: 01-11-2019 Through 03-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ICEMI46757.2019.9101453",
language = "English (US)",
series = "2019 14th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "559--566",
editor = "Juan Wu and Jiali Yin and Zhang Qi",
booktitle = "2019 14th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2019",
}