English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We propose a large displacement optical flow method that introduces a newstrategy to compute a good local minimum of any optical flow energy functional.The method requires a given set of discrete matches, which can be extremelysparse, and an energy functional which locally guides the interpolation fromthose matches. In particular, the matches are used to guide a structuredcoordinate-descent of the energy functional around these keypoints. It resultsin a two-step minimization method at the finest scale which is very robust tothe inevitable outliers of the sparse matcher and able to capture largedisplacements of small objects. Its benefits over other variational methodsthat also rely on a set of sparse matches are its robustness against very fewmatches, high levels of noise and outliers. We validate our proposal usingseveral optical flow variational models. The results consistently outperformthe coarse-to-fine approaches and achieve good qualitative and quantitativeperformance on the standard optical flow benchmarks.

FALDOI: A new minimization strategy for large displacement variational optical flow