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

The paper introduces an accurate solution to dense orthographic Non-RigidStructure from Motion (NRSfM) in scenarios with severe occlusions or, likewise,inaccurate correspondences. We integrate a shape prior term into variationaloptimisation framework. It allows to penalize irregularities of thetime-varying structure on the per-pixel level if correspondence qualityindicator such as an occlusion tensor is available. We make a realisticassumption that several non-occluded views of the scene are sufficient toestimate an initial shape prior, though the entire observed scene may exhibitnon-rigid deformations. Experiments on synthetic and real image data show thatthe proposed framework significantly outperforms state of the art methods forcorrespondence establishment in combination with the state of the art NRSfMmethods. Together with the profound insights into optimisation methods,implementation details for heterogeneous platforms are provided.

Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions