Optical Flow on Evolving Surfaces with Space and Time Regularisation
This work addresses motion estimation in biological imaging for researchers studying dynamic processes, but it appears incremental as it adapts existing variational methods to a new geometric context.
The paper tackled the problem of estimating optical flow for images on evolving surfaces, extending traditional methods to a dynamic non-Euclidean setting, and demonstrated its application on volumetric microscopy images of a live zebrafish embryo.
We extend the concept of optical flow with spatiotemporal regularisation to a dynamic non-Euclidean setting. Optical flow is traditionally computed from a sequence of flat images. The purpose of this paper is 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.