Optical Flow on Evolving Surfaces with an Application to the Analysis of 4D Microscopy Data
This work addresses motion estimation in biological imaging for researchers studying dynamic processes in live organisms, but it is incremental as it adapts existing variational methods to a new geometric context.
The paper tackles the problem of estimating motion (optical flow) for images on evolving surfaces, extending traditional flat-image methods to a dynamic non-Euclidean setting, and applies it to analyze 4D microscopy data of a live zebrafish embryo.
We extend the concept of optical flow to a dynamic non-Euclidean setting. Optical flow is traditionally computed from a sequence of flat images. It is the purpose of this paper to introduce variational motion estimation for images that are defined on an evolving surface. Volumetric microscopy images depicting a live zebrafish embryo serve as both biological motivation and test data.