Optical Flow on Evolving Surfaces with an Application to the Analysis of 4D Microscopy Data

TL;DR

This paper introduces a variational method for computing optical flow on evolving surfaces, extending traditional techniques to non-Euclidean settings, with applications demonstrated on 4D microscopy data of a zebrafish embryo.

Contribution

It presents a novel approach to estimate motion on dynamic surfaces, bridging a gap in optical flow analysis for non-flat, evolving geometries.

Findings

Successfully applied to 4D microscopy data of zebrafish embryo

Demonstrates effective motion estimation on non-Euclidean surfaces

Extends optical flow techniques to dynamic, evolving geometries

Abstract

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.