Defocus Particle Imaging for 3D Flow Characterization

The future development of flow characterization methods for small scale fluid dynamics with limited optical access will further go in the direction of particle tracking methods based on defocusing, with algorithms relying on machine learning and neural networks. These methods are based on conventional micro-PIV setups, but have the potential to achieve unprecedented performance in terms of resolution, accuracy, robustness and speed. Together with the development of new algorithms, it is crucial to establish a systematic and widely-accepted framework for evaluation and comparison of the different methods. This aspect has generally been overlooked, and most research groups test their own methods on their own dataset, making it impossible to give a fair comparison and to effectively quantify the advancement of the processing techniques. Therefore, papers are expected that cover: 1. current and future requirements of defocus particle imaging techniques for interdisciplinary applications 2. state of current advanced algorithms and future perspectives for defocus particle imaging