TomoFluid: Reconstructing Dynamic Fluid From Sparse View Videos
Guangming Zang,  Ramzi Idoughi,  Congli Wang,  Anthony Bennett,  Jianguo Du,  Scott Skeen,  William L. Roberts,  Peter Wonka,  Wolfgang Heidrich

Visible light tomography is a promising and increasingly popular technique for fluid imaging. However, the use of a sparse number of viewpoints in the capturing setups makes the reconstruction of fluid flows very challenging. In this paper, we present a state-of-the-art 4D tomographic reconstruction framework that integrates several regularizers into a multi-scale matrix free optimization algorithm. In addition to existing regularizers, we propose two new regularizers for improved results: a regularizer based on view interpolation of projected images and a regularizer to encourage reprojection consistency. We demonstrate our method with extensive experiments on both simulated and real data.