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 new technique for computing dense scene flow from two handheldvideos with wide camera baselines and different photometric properties due todifferent sensors or camera settings like exposure and white balance. Ourtechnique innovates in two ways over existing methods: (1) it supportsindependently moving cameras, and (2) it computes dense scene flow forwide-baseline scenarios.We achieve this by combining state-of-the-artwide-baseline correspondence finding with a variational scene flow formulation.First, we compute dense, wide-baseline correspondences using DAISY descriptorsfor matching between cameras and over time. We then detect and replace occludedpixels in the correspondence fields using a novel edge-preserving Laplaciancorrespondence completion technique. We finally refine the computedcorrespondence fields in a variational scene flow formulation. We show densescene flow results computed from challenging datasets with independentlymoving, handheld cameras of varying camera settings.

Dense Wide-Baseline Scene Flow From Two Handheld Video Cameras