Abstracts

Despite significant recent progress, dense, time-resolved imaging of complex, non-stationary 3D flow velocities remains an elusive goal. This work tackles this problem by extending an established 2D method, Particle Imaging Velocimetry, to three dimensions by encoding depth into color. The encoding is achieved by illuminating the flow volume with a continuum of light planes (a rainbow), such that each depth corresponds to a specific wavelength of light. A diffractive component in the camera optics ensures that all planes are in focus simultaneously. With this setup, a single color camera is sufficient to track 3D trajectories of particles by combining 2D spatial and 1D color information.For reconstruction, this thesis derives an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. The proposed method is evaluated by both simulations and an experimental prototype setup. Despite significant recent progress, dense, time-resolved imaging of complex, non-stationary 3D flow velocities remains an elusive goal. This work tackles this problem by extending an established 2D method, Particle Imaging Velocimetry, to three dimensions by encoding depth into color. The encoding is achieved by illuminating the flow volume with a continuum of light planes (a rainbow), such that each depth corresponds to a specific wavelength of light. A diffractive component in the camera optics ensures that all planes are in focus simultaneously. With this setup, a single color camera is sufficient to track 3D trajectories of particles by combining 2D spatial and 1D color information.For reconstruction, this thesis derives an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. The proposed method is evaluated by both simulations and an experimental prototype setup.Advisors/Committee Members: Heidrich, Wolfgang, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Thoroddsen, Sigurdur T., Hadwiger, Markus.