Abstract

We present a global optimization approach to optical flflow estimation. The approach optimizes a classical optical flflow objective over the full space of mappings between discrete grids. No descriptor matching is used. The highly regular structure of the space of mappings enables optimizations that reduce the computational complexity of the algorithm’s inner loop from quadratic to linear and support effifi- cient matching of tens of thousands of nodes to tens of thousands of displacements. We show that one-shot global optimization of a classical Horn-Schunck-type objective over regular grids at a single resolution is suffificient to initialize continuous interpolation and achieve state-of-the-art performance on challenging modern benchmarks